Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks | Paper Citation Record

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This paper cites Highway Networks.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Highway Networks

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This paper cites ”Deep residual learning for image recognition.” Proceedings of the IEEE conference on computer vision and pattern recognition.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Deep residual learning for image recognition.” Proceedings of the IEEE conference on computer vision and pattern recognition

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This paper cites ”Deep networks with stochastic depth.” Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Nether- lands, October 11–14, 2016, Proceedings, Part IV 14.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Deep networks with stochastic depth.” Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Nether- lands, October 11–14, 2016, Proceedings, Part IV 14

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This paper cites ”Densely connected convolutional networks.” Proceed- ings of the IEEE conference on computer vision and pattern recognition.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Densely connected convolutional networks.” Proceed- ings of the IEEE conference on computer vision and pattern recognition

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This paper cites ”On the use of artificial neural networks in simulation-based manufacturing control.” Journal of Simulation 8.1 (2014): 76-90.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”On the use of artificial neural networks in simulation-based manufacturing control.” Journal of Simulation 8.1 (2014): 76-90

Reference 6

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This paper cites ”Deep learning.” nature 521.7553 (2015): 436-444.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Deep learning.” nature 521.7553 (2015): 436-444

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This paper cites ”Searching for exotic particles in high-energy physics with deep learning.” Nature communica- tions 5.1 (2014): 4308.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Searching for exotic particles in high-energy physics with deep learning.” Nature communica- tions 5.1 (2014): 4308

Reference 8

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This paper cites ”Forecasting S&P 500 index using artificial neural networks and design of experiments.” Journal of Industrial Engineering International 9 (2013): 1-9.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Forecasting S&P 500 index using artificial neural networks and design of experiments.” Journal of Industrial Engineering International 9 (2013): 1-9

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This paper cites ”Neural networks applied to discriminate botanical origin of honeys.” Food chemistry 175 (2015): 128-136.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Neural networks applied to discriminate botanical origin of honeys.” Food chemistry 175 (2015): 128-136

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Observation fc0b29ee-3cc6-4bf8-a09d-4bbada56602a · outbound

This paper cites ”Applications of arti- ficial neural networks in health care organizational decision-making: A scoping review.” PloS one 14.2 (2019): e0212356.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Applications of arti- ficial neural networks in health care organizational decision-making: A scoping review.” PloS one 14.2 (2019): e0212356

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This paper cites Fienberg.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Fienberg

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This paper cites ”Predicting good prob- abilities with supervised learning.” Proceedings of the 22nd international conference on Machine learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Predicting good prob- abilities with supervised learning.” Proceedings of the 22nd international conference on Machine learning

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This paper cites ”On calibration of modern neural networks.” Inter- national conference on machine learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”On calibration of modern neural networks.” Inter- national conference on machine learning

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This paper cites End to End Learning for Self-Driving Cars.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks End to End Learning for Self-Driving Cars

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This paper cites ”Calibrating predictive model estimates to support personalized medicine.” Journal of the American Medical Informatics Association 19.2 (2012): 263-274.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Calibrating predictive model estimates to support personalized medicine.” Journal of the American Medical Informatics Association 19.2 (2012): 263-274

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This paper cites ”Predicting with confidence and tolerance.” Nature methods 15.11 (2018): 843-845.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Predicting with confidence and tolerance.” Nature methods 15.11 (2018): 843-845

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This paper cites ”Errors in predictor variables.” (2024): 4-6.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Errors in predictor variables.” (2024): 4-6

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Observation 105e4fca-76ca-4275-a810-3ba6e6ca4e4b · outbound

This paper cites ”Probabilistic machine learning and artificial in- telligence.” Nature 521.7553 (2015): 452-459.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Probabilistic machine learning and artificial in- telligence.” Nature 521.7553 (2015): 452-459

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This paper cites ”Simple and scalable predictive uncertainty estimation using deep en- sembles.” Advances in neural information processing systems 30 (2017).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Simple and scalable predictive uncertainty estimation using deep en- sembles.” Advances in neural information processing systems 30 (2017)

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Observation b52e0825-794a-4365-90c9-c46f9c012228 · outbound

This paper cites ”Dropout as a bayesian approxi- mation: Representing model uncertainty in deep learning.” international conference on machine learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Dropout as a bayesian approxi- mation: Representing model uncertainty in deep learning.” international conference on machine learning

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This paper cites Neural Processes.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Neural Processes

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This paper cites ”Classification with Bayesian neural networks.” Ma- chine Learning Challenges Workshop.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Classification with Bayesian neural networks.” Ma- chine Learning Challenges Workshop

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This paper cites ”A practical Bayesian framework for backpropaga- tion networks.” Neural computation 4.3 (1992): 448-472.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”A practical Bayesian framework for backpropaga- tion networks.” Neural computation 4.3 (1992): 448-472

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This paper cites ”Weight uncertainty in neural network.” Inter- national conference on machine learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Weight uncertainty in neural network.” Inter- national conference on machine learning

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This paper cites ”What uncertainties do we need in bayesian deep learning for computer vision?.” Advances in neural in- formation processing systems 30 (2017).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”What uncertainties do we need in bayesian deep learning for computer vision?.” Advances in neural in- formation processing systems 30 (2017)

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This paper cites ”Non- parametric calibration for classification.” International Conference on Artificial Intelligence and Statistics.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Non- parametric calibration for classification.” International Conference on Artificial Intelligence and Statistics

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This paper cites Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Detecting misclassification errors in neural networks with a gaussian process model.” Proceedings of the AAAI Conference on Artificial Intelligence

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This paper cites ”Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers.” Icml.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers.” Icml

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Unresolved cited work

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Ob- taining well calibrated probabilities using bayesian binning.” Proceedings of the AAAI conference on artificial intelligence

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This paper cites Distilling the Knowledge in a Neural Network.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Distilling the Knowledge in a Neural Network

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Information theory and statistical mechanics

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”The elements of statistical learning: Data mining, inference, and prediction.” (2009)

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This paper cites McAuliffe.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks McAuliffe

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This paper cites Towards Improved Variational Inference for Deep Bayesian Models.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Towards Improved Variational Inference for Deep Bayesian Models

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This paper cites Deep Neural Networks as Gaussian Processes.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Deep Neural Networks as Gaussian Processes

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Deep kernel learning.” Artificial intel- ligence and statistics

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Revisiting unreasonable effectiveness of data in deep learning era.” Proceedings of the IEEE international conference on computer vision

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Unresolved cited work

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Deep learning for remote sensing data: A technical tutorial on the state of the art.” IEEE Geoscience and remote sensing magazine 4.2 (2016): 22-40

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Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”A comprehensive survey on SAR ATR in deep- learning era.” Remote Sensing 15.5 (2023): 1454

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This paper cites ”Change detection in synthetic aperture radar images based on deep neural networks.” IEEE transactions on neural networks and learning systems 27.1 (2015): 125-138.

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Observation 87a6d9d3-5bdf-4d6a-ab20-0a61fd98a990 · outbound

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.090719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6842020e-daff-4be5-af88-d41586fb5ffc · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T15:27:30.629585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11665f85-bc44-4e9f-ae81-1ee2065d693d · outbound

This paper cites ”Rethinking the inception architecture for computer vision.” Proceedings of the IEEE conference on computer vision and pattern recognition.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Rethinking the inception architecture for computer vision.” Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.082384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e0a2989b-fa79-4001-ae84-eae48e98ec25 · outbound

This paper cites an unresolved cited work.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:27:31.074295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8eb5183c-af41-42c8-a45d-de425e10e475 · outbound

This paper cites Lawrence.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Lawrence

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.066335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb189e91-b472-4d0e-b7e9-55ba33c132bb · outbound

This paper cites ”Multi-task Gaussian process prediction.” Advances in neural information processing systems 20 (2007).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Multi-task Gaussian process prediction.” Advances in neural information processing systems 20 (2007)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.058812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b171ea9f-c8cb-49e4-ad8a-5dee18430ee2 · outbound

This paper cites Lawrence.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Lawrence

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.050871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a117c12e-83e3-4bbe-b7f2-8a1aa0536521 · outbound

This paper cites ”It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals.” Advances in neural information processing systems 26 (2013).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals.” Advances in neural information processing systems 26 (2013)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.042949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8600c912-f16d-4915-8416-dd931e4e4c28 · outbound

This paper cites ”Simple and principled uncertainty estimation with deterministic deep learning via distance awareness.” Advances in neural information processing systems 33 (2020): 7498-7512.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Simple and principled uncertainty estimation with deterministic deep learning via distance awareness.” Advances in neural information processing systems 33 (2020): 7498-7512

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.033860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 46eccebc-4bf4-4cfa-9389-c944cd0c423b · outbound

This paper cites ”Gaussian processes for regression.” Advances in neural information processing systems 8 (1995).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Gaussian processes for regression.” Advances in neural information processing systems 8 (1995)

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.025791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eb69d282-2fc6-46f4-96b5-77c2a6f1e981 · outbound

This paper cites Gaussian pro- cesses for machine learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Gaussian pro- cesses for machine learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.017824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 00e2ec9f-6e38-4b03-9e9b-3f6d41100b4e · outbound

This paper cites an unresolved cited work.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:27:31.009842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7a1d616d-8e86-4495-b32f-b2f197297f95 · outbound

This paper cites Lawrence, and Magnus Rattray.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Lawrence, and Magnus Rattray

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.001308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2c3f916a-0e58-4398-801d-04872c3f8d9f · outbound

This paper cites Lawrence.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Lawrence

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.993433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 14caaeac-b378-4a6e-ab3f-aeb34b843b6a · outbound

This paper cites Lawrence.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Lawrence

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.985525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c17724f9-f960-4f7c-9c59-7c971ceb3317 · outbound

This paper cites ”Doubly stochastic variational inference for deep Gaussian processes.” Advances in neural information processing systems 30 (2017).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Doubly stochastic variational inference for deep Gaussian processes.” Advances in neural information processing systems 30 (2017)

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.977270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e5cf59da-e79e-4637-8561-894e65f211ab · outbound

This paper cites Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T15:27:30.668571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3015085-38bd-4854-88c5-d135bf91f82c · outbound

This paper cites Deep learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Deep learning

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.969526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f5e0916f-c00a-41ce-bfa7-cea15d220eda · outbound

This paper cites ”Risk versus uncertainty in deep learning: Bayes, bootstrap and the dangers of dropout.” NIPS workshop on bayesian deep learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Risk versus uncertainty in deep learning: Bayes, bootstrap and the dangers of dropout.” NIPS workshop on bayesian deep learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.961810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ff85d53a-355b-4987-a317-77c1cc39f783 · outbound

This paper cites ”Bayesian deep learning and a probabilistic perspective of generalization.” Advances in neural information processing systems 33 (2020): 4697-4708.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Bayesian deep learning and a probabilistic perspective of generalization.” Advances in neural information processing systems 33 (2020): 4697-4708

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.953656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7241333a-1ad6-4564-aea6-a64e6883c736 · outbound

This paper cites ”Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift.” Advances in neural information processing systems 32 (2019).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift.” Advances in neural information processing systems 32 (2019)

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.945115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e0a2a9ee-a610-47d3-9598-82e26853d639 · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

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Resolution: unresolved; no resolver link, observed 2026-08-06T15:27:30.682348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db2a266e-103d-488d-ab67-ea59a87afd3f · outbound

This paper cites ”Accurate uncertainties for deep learning using calibrated regression.” International conference on machine learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Accurate uncertainties for deep learning using calibrated regression.” International conference on machine learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:31.224878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7113a13e-21ad-43f7-895f-4383ea41e898 · outbound

This paper cites ”A simple baseline for bayesian uncertainty in deep learning.” Advances in neural information processing systems 32 (2019).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”A simple baseline for bayesian uncertainty in deep learning.” Advances in neural information processing systems 32 (2019)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.936766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fdbdac49-42f6-47fa-910c-3fd931a96a51 · outbound

This paper cites ”Finding structure in time.” Cognitive science 14.2 (1990): 179-211.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Finding structure in time.” Cognitive science 14.2 (1990): 179-211

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.928663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f79cfef0-3da3-43ba-8849-98481b6a634e · outbound

This paper cites ”Long short-term memory.” Neural computation 9.8 (1997): 1735-1780.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Long short-term memory.” Neural computation 9.8 (1997): 1735-1780

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.920317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c0a84ef-9249-422e-b59a-98c7b2776324 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T15:27:30.695841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa4f2a3d-98c4-4c51-94c7-47e6d5b9c1b7 · outbound

This paper cites ”Gradient-based learning applied to document recognition.” Proceedings of the IEEE 86.11 (2002): 2278-2324.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Gradient-based learning applied to document recognition.” Proceedings of the IEEE 86.11 (2002): 2278-2324

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.910616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 622d0aea-fe6d-453c-8ea1-587b7085cfa3 · outbound

This paper cites The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T15:27:30.701756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7e44dbb-1c00-411f-882c-aa0e9d486937 · outbound

This paper cites an unresolved cited work.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:27:30.902156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5b4c1ba9-a0eb-4807-9a12-69f2a75345ef · outbound

This paper cites Adaptive Residual Transformation for Enhanced Feature-Based OOD Detection in SAR Imagery.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks Adaptive Residual Transformation for Enhanced Feature-Based OOD Detection in SAR Imagery

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Resolution: verified exact; local_arxiv, observed 2026-08-06T15:27:30.746796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 84aabb89-1480-4ac4-8b58-cbc953da1013 · outbound

This paper cites [On- line].

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks [On- line]

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.893546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 22a63da7-4d0a-42dd-8c65-45c028ac56f9 · outbound

This paper cites ”Trainable calibration measures for neural networks from kernel mean embeddings.” Interna- tional Conference on Machine Learning.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Trainable calibration measures for neural networks from kernel mean embeddings.” Interna- tional Conference on Machine Learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.885275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 84e2b571-7a59-4cfa-ac97-74ddbc8cf80e · outbound

This paper cites ”Beyond temperature scaling: Obtaining well- calibrated multi-class probabilities with dirichlet calibration.” Advances in neural information processing systems 32 (2019).

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Beyond temperature scaling: Obtaining well- calibrated multi-class probabilities with dirichlet calibration.” Advances in neural information processing systems 32 (2019)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:27:30.876525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers