Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum | Paper Citation Record

Observation 9df5c8f5-e22d-471d-9f2c-9e3b2b077f7c · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.963263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be4a2990-d4f2-4aa9-8fee-683c8bb25c07 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.967584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c97a279b-940e-497a-9f06-3a079ef2f343 · outbound

This paper cites IEEE/ACM Transactions on Audio, Speech, and Language Processing29, 745–755 (2021).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum IEEE/ACM Transactions on Audio, Speech, and Language Processing29, 745–755 (2021)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.971344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b8bed51-4c18-4434-9b66-050a9a0293ac · outbound

This paper cites Neural computation 9(8), 1735–1780 (1997).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Neural computation 9(8), 1735–1780 (1997)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.975184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bf27833-90e5-477c-85a9-078fa5459c17 · outbound

This paper cites In: Proceedings, vol.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings, vol

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.098278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ff49558b-fbae-4475-b9a2-dbbcfc825120 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.088981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1de38e7b-5730-47ce-8c3d-25172a6eba2b · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.985630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74dcb4ce-8136-4d34-ac50-e4d4f8d79816 · outbound

This paper cites Language Modeling with Deep Transformers.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Language Modeling with Deep Transformers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.989337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 621ba981-383d-4257-aa0e-33bc53686537 · outbound

This paper cites Advances in neural information processing systems28 (2015).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems28 (2015)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.079140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b5f16d30-356e-44b7-a3b9-85f204c9a76a · outbound

This paper cites Exploring Sparsity in Recurrent Neural Networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Exploring Sparsity in Recurrent Neural Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.996323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 486face0-38a9-4605-97a2-059dd90ca687 · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:07.999746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3254636-5cc6-48cf-ae36-8ae94f91928c · outbound

This paper cites The State of Sparsity in Deep Neural Networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum The State of Sparsity in Deep Neural Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.003589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84099917-3a59-4109-9841-95d614e6cba9 · outbound

This paper cites Neurocomputing390, 327–340 (2020) 20.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Neurocomputing390, 327–340 (2020) 20

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.070041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2796368d-c7b0-480e-ab73-444b917d4193 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.010166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75a39c31-dcdf-4f93-94c7-5694f15f32ca · outbound

This paper cites Soft Weight-Sharing for Neural Network Compression.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Soft Weight-Sharing for Neural Network Compression

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.013626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6b20a92-6f3d-4c58-9d88-6fa833325291 · outbound

This paper cites International Journal of Computer Vision129, 1789–1819 (2021).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum International Journal of Computer Vision129, 1789–1819 (2021)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.061121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 644002ab-761c-43ff-8663-b4621d54e7d8 · outbound

This paper cites Lyapunov-Guided Representation of Recurrent Neural Network Performance.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Lyapunov-Guided Representation of Recurrent Neural Network Performance

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:27:08.551781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 178aa450-ff76-4bdf-a0c5-95962df30937 · outbound

This paper cites Journal of Machine Learning Research22(241), 1–124 (2021).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Journal of Machine Learning Research22(241), 1–124 (2021)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.051551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ff1b4030-f285-4362-93ec-33eea3b488da · outbound

This paper cites arXiv e-prints, 2103 (2021).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum arXiv e-prints, 2103 (2021)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.041592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4b41fad6-1125-4e15-98a0-184049ca28f6 · outbound

This paper cites Physical Review A 39(12), 6600 (1989).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Physical Review A 39(12), 6600 (1989)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.031583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation affe7974-1396-4b5a-8d0e-48f5111e196f · outbound

This paper cites Connection Science1(1), 3–16 (1989).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Connection Science1(1), 3–16 (1989)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.021383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 28ded078-b638-4f48-8b4d-124f6593c1f1 · outbound

This paper cites Advances in neural information processing systems1(1988).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems1(1988)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.011547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a396ae1f-652e-4c49-91e5-3a7410ac561e · outbound

This paper cites Advances in neural information processing systems2(1989).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems2(1989)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:09.000601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 734d7490-6181-45d5-b5e4-997ff45472f7 · outbound

This paper cites Advances in neural information processing systems5(1992).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems5(1992)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.041767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b580e32f-1f48-453f-9409-2152ba6c5f65 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Pruning Filters for Efficient ConvNets

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.044634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f3d780f-e9a4-416d-88ba-a3a6418f9a84 · outbound

This paper cites Advances in neural information processing systems29(2016).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems29(2016)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.982603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation acc1086d-55b6-4241-b378-7616fee61af2 · outbound

This paper cites In: Proceedings of the European Conference on Computer Vision (ECCV), pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings of the European Conference on Computer Vision (ECCV), pp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.972057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b732994e-7dba-4c84-9a2a-176aa1920ebf · outbound

This paper cites Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.054378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d360e4a9-f023-432a-8bdf-b062e7c02eea · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.962607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c541e29d-f25e-4403-ab20-2e53a41b2c2a · outbound

This paper cites Pruning Convolutional Neural Networks for Resource Efficient Inference.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Pruning Convolutional Neural Networks for Resource Efficient Inference

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.060672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b2b91de-dc8f-4be2-a38d-a932612981f4 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.952426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9bdf4cfe-81c4-45a4-acff-8525736100f6 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.942707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 54739359-2304-4417-b77a-82514b092a27 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.932987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 69511c30-e947-4957-807e-9e8b2df8b64a · outbound

This paper cites Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers

Reference 34

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:27:08.511892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f041de11-7a1c-495e-80dd-27ef51d36c03 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.923053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a0153aa3-4d9d-4222-9c95-bc05c720369a · outbound

This paper cites Dynamic Model Pruning with Feedback.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Dynamic Model Pruning with Feedback

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.079959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d409050-df21-477b-8385-7d0d7a2bed6c · outbound

This paper cites Learning Sparse Neural Networks through $L_0$ Regularization.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Learning Sparse Neural Networks through $L_0$ Regularization

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.083226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abd52848-858d-4b1c-a1a3-13c9c8fb8b85 · outbound

This paper cites Learning Intrinsic Sparse Structures within Long Short-Term Memory.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Learning Intrinsic Sparse Structures within Long Short-Term Memory

Reference 38

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:27:08.480837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 22578977-a3da-44af-9127-285124f46e44 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.913529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4905764e-caa5-4078-9685-9b0ce5c615e2 · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.092640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c49c4ef7-7ee4-465b-bc43-af1abedeaf56 · outbound

This paper cites SNIP: Single-shot Network Pruning based on Connection Sensitivity.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum SNIP: Single-shot Network Pruning based on Connection Sensitivity

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.095872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d7043c7-c5ec-4e9a-9bad-a8f3009e7d1d · outbound

This paper cites A Signal Propagation Perspective for Pruning Neural Networks at Initialization.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum A Signal Propagation Perspective for Pruning Neural Networks at Initialization

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.099294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a75551b0-eea2-4f65-b1af-8522cd30e42a · outbound

This paper cites Picking Winning Tickets Before Training by Preserving Gradient Flow.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Picking Winning Tickets Before Training by Preserving Gradient Flow

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.102709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4296d6a1-eaac-4210-9849-545c17780be4 · outbound

This paper cites Advances in Neural Information Processing Systems33, 6377–6389 (2020).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in Neural Information Processing Systems33, 6377–6389 (2020)

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.904012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d4a8131b-bc38-4e64-b15a-8676537f969e · outbound

This paper cites Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks

Reference 45

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:27:08.430472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d0e05dfe-9b20-4ddc-9a8a-5c264c44b39a · outbound

This paper cites Deep Rewiring: Training very sparse deep networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Deep Rewiring: Training very sparse deep networks

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.112978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca659678-7bab-4420-a75b-28852549bdef · outbound

This paper cites IEEE Transactions on Computers68(10), 1487–1497 (2019).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum IEEE Transactions on Computers68(10), 1487–1497 (2019)

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.893507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bfc4c0f1-f4e5-40cf-adec-7367d62917ac · outbound

This paper cites Nature communications9(1), 1–12 (2018).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Nature communications9(1), 1–12 (2018)

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.883240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8c545ce9-eeac-4282-831a-c35b14cdccb2 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.872990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7446cd7-0245-4e81-867b-7c8c54889992 · outbound

This paper cites Sparse Networks from Scratch: Faster Training without Losing Performance.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Sparse Networks from Scratch: Faster Training without Losing Performance

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.126151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63785594-9703-4d74-aa77-fe71bc3f02b5 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.862682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1cee9051-7ce3-4e45-8ccd-002a6f4ac9d5 · outbound

This paper cites Advances in Neural Information Processing Systems33, 20744–20754 (2020).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in Neural Information Processing Systems33, 20744–20754 (2020)

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.852671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 61a5c83f-d549-4bd3-bd88-d55cc84b5f69 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.842476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7f676979-0471-4f67-8d53-952670ca7b16 · outbound

This paper cites Pruning Neural Networks at Initialization: Why are We Missing the Mark?.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Pruning Neural Networks at Initialization: Why are We Missing the Mark?

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.138617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 425133a8-8ad5-46ec-9f20-66cb3ec8d1e6 · outbound

This paper cites Journal of machine learning research13(2) (2012).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Journal of machine learning research13(2) (2012)

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.141835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 287138f6-1fb8-4d4e-9050-3178556e00d4 · outbound

This paper cites Advances in neural information processing systems 25(2012).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems 25(2012)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.826620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 183c3fbd-1f08-4652-b4bf-a6299fb1b189 · outbound

This paper cites In: International Conference on Learning and Intelligent Optimization, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Learning and Intelligent Optimization, pp

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.816586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b0d9ef17-f003-4c6c-9c63-09ba2279ac2c · outbound

This paper cites Advances in neural information processing systems24(2011).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Advances in neural information processing systems24(2011)

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.150908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a442caa2-c5af-4948-b4d4-3ea4d9175ebc · outbound

This paper cites In: Pro- ceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Pro- ceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.800739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 77e8b165-9fa6-442f-86e5-0d7e7bf0b2ca · outbound

This paper cites In: NIPS Workshop on Bayesian Optimization in Theory and Practice (2013).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: NIPS Workshop on Bayesian Optimization in Theory and Practice (2013)

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.791689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6634c491-e46b-4422-bcf9-7d7e251c494c · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.782474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 602a876e-56e2-4ef4-a3cc-9e7018da9454 · outbound

This paper cites Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.163513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 106e7eeb-4167-481b-8643-00f92ec7be24 · outbound

This paper cites The journal of machine learning research18(1), 6765–6816 (2017).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum The journal of machine learning research18(1), 6765–6816 (2017)

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.773230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bdfd1587-4abe-4c99-8643-f13ab8dad709 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Machine Learning, pp

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.764069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85581ed9-7284-4859-adc2-c471a900c7c8 · outbound

This paper cites AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks

Reference 65

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:27:08.380777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 395a8259-1cde-4faa-aed5-a51fde0a02f2 · outbound

This paper cites R-FORCE: Robust Learning for Random Recurrent Neural Networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum R-FORCE: Robust Learning for Random Recurrent Neural Networks

Reference 66

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:27:08.368080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8ab05760-def6-4ea9-9513-cbbd40cb2c88 · outbound

This paper cites Frontiers in Applied Mathematics and Statistics8(2022) https://doi.org/ 10.3389/fams.2022.818799.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Frontiers in Applied Mathematics and Statistics8(2022) https://doi.org/ 10.3389/fams.2022.818799

Reference 67

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T05:27:08.354378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 604c89c0-cc31-448b-8db2-fb373b4257f7 · outbound

This paper cites In: Interna- tional Conference on Artificial Intelligence and Statistics, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Interna- tional Conference on Artificial Intelligence and Statistics, pp

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.754901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 04ae4e6d-f3b2-499c-9ade-c6c8859b28d5 · outbound

This paper cites Physical review letters105(26), 268104 (2010).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Physical review letters105(26), 268104 (2010)

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.745737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6e004e9e-d2d6-490f-89fc-c86ca890ff14 · outbound

This paper cites Lyapunov spectra of chaotic recurrent neural networks.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Lyapunov spectra of chaotic recurrent neural networks

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.189700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af647e8e-b834-4366-a184-81d7fe73cabb · outbound

This paper cites Dynamical systems, 1–43 (1995).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Dynamical systems, 1–43 (1995)

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.737129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c361a374-d87f-4596-86df-431f74120eb6 · outbound

This paper cites In: Stochastic Behavior in Classical and Quantum Hamiltonian Systems, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: Stochastic Behavior in Classical and Quantum Hamiltonian Systems, pp

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.727981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 691b3f34-0523-4436-8700-91915a59bd99 · outbound

This paper cites Dynamics and Stability of Systems14(2), 183–201 (1999).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Dynamics and Stability of Systems14(2), 183–201 (1999)

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.718029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74ba21a6-cfdb-48d4-a0f8-887bc6f7c9c9 · outbound

This paper cites Neural networks20(3), 323–334 (2007).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Neural networks20(3), 323–334 (2007)

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.708797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8eb01e95-dc13-4c57-816e-6066236a44b4 · outbound

This paper cites In: International Conference on Artificial Intelligence and Statistics, pp.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum In: International Conference on Artificial Intelligence and Statistics, pp

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.699206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fba2e746-70a6-4557-81fb-d34e43992eee · outbound

This paper cites A recurrent neural network without chaos.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum A recurrent neural network without chaos

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.208585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 883782a3-46ec-452c-bcb4-082130731bc6 · outbound

This paper cites Physical review letters73(14), 1927 (1994).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Physical review letters73(14), 1927 (1994)

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.689798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1212f13f-efea-4a49-89aa-d0917437bfb4 · outbound

This paper cites Journal of Nonlinear Science1(2), 175–199 (1991).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Journal of Nonlinear Science1(2), 175–199 (1991)

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.679918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8b0d3a7d-e244-4a4d-bfa4-43473c76ead4 · outbound

This paper cites Physica A: Statistical Mechanics and its Applications292(1-4), 182–192 (2001) 25.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Physica A: Statistical Mechanics and its Applications292(1-4), 182–192 (2001) 25

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.668803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a98185ca-f7c6-4fcf-8e06-2e5fe879ae6b · outbound

This paper cites Physical Review Letters51(16), 1442 (1983).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Physical Review Letters51(16), 1442 (1983)

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.657945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 33cc186f-7315-43e5-8e36-50b91af5bddb · outbound

This paper cites Progress of theoretical physics79(6), 1265–1268 (1988).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Progress of theoretical physics79(6), 1265–1268 (1988)

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.648045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cde96d7c-107b-4595-b262-20184f935129 · outbound

This paper cites Neural Computing and Applications36(34), 21211– 21226 (2024).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Neural Computing and Applications36(34), 21211– 21226 (2024)

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.638528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 43e2bd5c-5c17-43cc-9cf6-36a5aac76a76 · outbound

This paper cites Using Large Corpora, 273 (1994).

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Using Large Corpora, 273 (1994)

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:08.628323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 61163268-4c37-46d3-800f-ffc5c18ba489 · outbound

This paper cites Pointer Sentinel Mixture Models.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Pointer Sentinel Mixture Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.235260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers