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Paper Citation Record · LEDGER

Dying ReLU and Initialization: Theory and Numerical Examples

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1903.06733.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1903.06733 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:52:38.970034Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T07:09:38.437806Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 83e3d629-1fa3-4f97-b01d-6efcce177fd8 · inbound

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators cites this paper.

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Dying ReLU and Initialization: Theory and Numerical Examples

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:17:25.310784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T03:17:25.281108Z digest=sha256:908f75b22525e5261672f61a541773b2f03cda1f39e679e3df9504b5e3132464

Observation 44655a1b-e57b-4df3-9a57-4a12b0832b92 · inbound

STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution cites this paper.

STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution Dying ReLU and Initialization: Theory and Numerical Examples

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T23:52:38.970034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:52:38.970034Z digest=sha256:eb32781af422d6e05f2a265637df35a9b50d59be036658c96e19fcc3e76d2118

Observation d717e8d7-65e4-46d2-a40c-dc2188495c62 · inbound

TinyProto: Communication-Efficient Federated Learning with Sparse Prototypes in Resource-Constrained Environments cites this paper.

TinyProto: Communication-Efficient Federated Learning with Sparse Prototypes in Resource-Constrained Environments Dying ReLU and Initialization: Theory and Numerical Examples

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T19:58:04.270657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:58:04.270657Z digest=sha256:cb513ba5f074749867f648b4cf8534063bc918f4c8d5b0b3d019cd29fd330d31

Observation 8a2f37cb-ecd2-4520-9ae7-3c96f4226fd0 · inbound

4D-MISR: A unified model for low-dose super-resolution imaging via feature fusion cites this paper.

4D-MISR: A unified model for low-dose super-resolution imaging via feature fusion Dying ReLU and Initialization: Theory and Numerical Examples

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T17:49:30.173172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:49:30.173172Z digest=sha256:2c5ea3ced5f6b04eb160870314fa3a65ff715f6b045a6f0acdfffc79168aaed0

Observation df1e04ef-e002-4421-b7b4-dc71ddd32eed · inbound

Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks cites this paper.

Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks Dying ReLU and Initialization: Theory and Numerical Examples

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T13:54:40.117887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:54:40.117887Z digest=sha256:21a6699629d5a95e303c6f7215da9518fe15b710a113edb1e3d7a170db210fc1

Observation ad8daf11-8d6c-4266-a6e0-e8e46ae36001 · inbound

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes cites this paper.

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes Dying ReLU and Initialization: Theory and Numerical Examples

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:48:19.641175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T13:46:32.405079Z digest=sha256:4d14f0fddcb7ba60db48f73ad9eeffafcf573c932b79587d1e0ecf2cbbcbe4fc

Observation ca9507fc-f464-4af7-9f8c-3bd8038cb2a7 · inbound

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes cites this paper.

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes Dying ReLU and Initialization: Theory and Numerical Examples

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:16:19.677693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-22T09:15:32.395442Z digest=sha256:268a1b48588636d46268bf1c1d57c7c75e5330303477019271e7ab1dff64f2f2

Observation 42fc4e89-9e5c-40bf-840e-7b3a9af88f86 · inbound

Preserving Plasticity in Continual Learning via Dynamical Isometry cites this paper.

Preserving Plasticity in Continual Learning via Dynamical Isometry Dying ReLU and Initialization: Theory and Numerical Examples

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:07:28.515553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T17:26:20.769515Z digest=sha256:b4608d4367cb3d853442cb42294258529b112f965e219a5e3f8f47eadc94c609

Observation 33f75801-431f-47ae-a5e9-74ad184df649 · inbound

NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning cites this paper.

NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning Dying ReLU and Initialization: Theory and Numerical Examples

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:19:37.636482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T14:39:59.778081Z digest=sha256:edeac6965c7e711b33a4442591528de92640065bf90e2df234f7657d9a8d715a

Observation 6899582e-2e48-4637-884b-447fe454293f · inbound

Interpretable Material Spatial Intelligence for Discovery of Governing Microstructural Features cites this paper.

Interpretable Material Spatial Intelligence for Discovery of Governing Microstructural Features Dying ReLU and Initialization: Theory and Numerical Examples

Reference 96

Resolution
malformed identifier
arxiv_id, observed 2026-07-04T07:09:38.439286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T13:39:04.428631Z digest=sha256:25b23af01144b2258cb445e366997388e813b1cdadfaeaaefc5ebdd70fe21d0e

Observation 8fc7cb80-1a3c-44a9-b455-23815fc39d53 · inbound

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System cites this paper.

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System Dying ReLU and Initialization: Theory and Numerical Examples

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-11T10:24:00.719150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T10:24:00.719150Z digest=sha256:563d24f2c7fa3c530a3e33b6fd142579b4c733ec3cc5f75a9934e4b7395282d9