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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2507.15987.

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pith.paper-citation-record.v1
2507.15987 v1

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Outbound references

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This paper cites Highway Networks.

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

Reference 2

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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

Reference 3

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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

Reference 4

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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

Reference 5

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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

Reference 7

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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

Reference 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

Reference 10

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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

Reference 11

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This paper cites Fienberg.

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

Reference 12

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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

Reference 13

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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

Reference 14

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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

Reference 15

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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

Reference 16

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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

Reference 17

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

Reference 18

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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

Reference 19

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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)

Reference 20

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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

Reference 21

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

Reference 22

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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)

Reference 26

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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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This paper cites ”Detecting misclassification errors in neural networks with a gaussian process model.” Proceedings of the AAAI Conference on Artificial Intelligence.

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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This paper cites ”Ob- taining well calibrated probabilities using bayesian binning.” Proceedings of the AAAI conference on artificial intelligence.

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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Observation ed4a2f81-6ee5-40b8-a6c9-6a35756099d8 · outbound

This paper cites ”Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods.” Advances in large margin classifiers 10.3 (1999): 61-74.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods.” Advances in large margin classifiers 10.3 (1999): 61-74

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raw_fallback, observed 2026-08-06T15:27:31.176217Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.587416Z digest=sha256:fe15a7c1177b6bdad2394a90f84d84bef64b333a7da4e1165771b35fcf6171a9

Observation 1373d4b7-7fcc-4238-a1aa-92db7f013b72 · outbound

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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no resolver link, observed 2026-08-06T15:27:30.590034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:30.590034Z digest=sha256:19b9c2a9f103cfdcd2a1f1672dea78e751086ff748c7629108c15cb60bae01b9

Observation 11cb9dcf-a870-4517-acb3-763ccc20fd5e · outbound

This paper cites Information theory and statistical mechanics.

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

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.168357Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.593204Z digest=sha256:cb69d790ce67f2048d0357efa9464c1acd822742810ef2cb6ec30812e61dc67e

Observation 4c512fb5-228a-4efb-8049-b4e9a36736f0 · outbound

This paper cites ”The elements of statistical learning: Data mining, inference, and prediction.” (2009).

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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raw_fallback, observed 2026-08-06T15:27:31.160913Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.595737Z digest=sha256:61f490184e53f94ea84ab57ab18e818d28a9453be9f07f8bcddeb09b33a11f96

Observation 247bc34d-4981-4a12-8cd3-9c6d79a2977f · outbound

This paper cites McAuliffe.

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

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.152929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.598366Z digest=sha256:c0d781fcc224ca4dcff6833df4800ccceee0448ed941cd566f7dc205b04d76ab

Observation 8df6a4fb-1955-4983-bd0e-81c347346aee · outbound

This paper cites ”Ensemble deep learning: A review.” Engi- neering Applications of Artificial Intelligence 115 (2022): 105151.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Ensemble deep learning: A review.” Engi- neering Applications of Artificial Intelligence 115 (2022): 105151

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.145383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.600947Z digest=sha256:ed50c0db4a41907cc63ccab6dcb51de7499d2c7b222daca5ae7afc0689d3bac5

Observation 0e662a84-e759-40e7-a58a-d532caf39a4e · outbound

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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verified exact
local_arxiv, observed 2026-08-06T15:27:30.813229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.603303Z digest=sha256:90f71405e48f42ec084ffa4e75244236f4fc26bb3755396246e277505ca9c56f

Observation 20b61fe3-9c58-4883-b15a-98789fbc7e3f · outbound

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

Reference 41

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unresolved
no resolver link, observed 2026-08-06T15:27:30.605878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:30.605878Z digest=sha256:60b7e5a5f20724230e70cb97caa035bc63a17ce1e82105de86dcc6894d403533

Observation 873a4373-862a-4eb7-90c0-b6e801f694e1 · outbound

This paper cites ”Deep kernel learning.” Artificial intel- ligence and statistics.

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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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.137456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.608506Z digest=sha256:24168cd9db1fa27dadb9b115b13ebc1a1188d5e7b4666be74c7ea973656cee0b

Observation f5dc54b4-0225-4e52-8327-ec689a82d327 · outbound

This paper cites Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes.

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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verified exact
local_arxiv, observed 2026-08-06T15:27:30.792694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.611339Z digest=sha256:38ae5b9210aeef90e2006239a91a4e1ce9a07a47d0addaf57f709cff30394098

Observation 98e7b752-068a-442a-a3c3-673848287adf · outbound

This paper cites ”Revisiting unreasonable effectiveness of data in deep learning era.” Proceedings of the IEEE international conference on computer vision.

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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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.129732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.614379Z digest=sha256:30d96455d3b05473476dbb0547dfe58897371e43a0e9f2866e4495fc07a8b3cc

Observation 5605429c-8a8f-415e-abb9-709582cbf3bb · 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 45

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unresolved
raw_fallback, observed 2026-08-06T15:27:31.122076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.616801Z digest=sha256:dabd860210c01b86827f46398b9c34e285a40f52fedebcf4e91fcd426aad2499

Observation 3b987734-c814-4bd0-af99-b8d08c7ef2a2 · outbound

This paper cites ”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.

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

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.114435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.619430Z digest=sha256:c901a809405b943313f6746f825746f26df4e99861e66c4f053592fd698b11e1

Observation 2c007e14-f301-4b45-9557-1880f326c443 · outbound

This paper cites ”A comprehensive survey on SAR ATR in deep- learning era.” Remote Sensing 15.5 (2023): 1454.

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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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.106690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.622002Z digest=sha256:dc8fe85077b0766a0c95767fd9cafe366b4fde46a744d04b6498e7eb905a41d9

Observation 7609ad98-077a-4e49-817f-09cda947bd2a · outbound

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.

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

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:27:31.098952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.624498Z digest=sha256:db9f9de1218016b765de3b9105eceb26165930d2cb07d3f42547448a44f016bc

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

This paper cites ”Target classification using the deep convolutional networks for SAR images.” IEEE transactions on geoscience and remote sensing 54.8 (2016): 4806-4817.

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks ”Target classification using the deep convolutional networks for SAR images.” IEEE transactions on geoscience and remote sensing 54.8 (2016): 4806-4817

Reference 49

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.627123Z digest=sha256:e9e3dd3cd0b26e51a566db2f7d1a5f61206b87ee21bf3082bf1cb7f6f6050c4f

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:30.629585Z digest=sha256:fa03e50a7c56596587df023ba65a5d9e74dd8a6ce2fbeab488f192644cd6edc0

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.632268Z digest=sha256:cdc7f553773e4bed245e24d3241d9d26606866f5890cffd9d841ffea03d3df4d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.634749Z digest=sha256:749ee127cf77d996c8c0791707b3b74776be6a69b4486762eca32d9b1b51daea

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.637301Z digest=sha256:fd058fb1796b4653b9ea4f7778946f6570574fa934e452b8895fdbee0100a32e

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.639826Z digest=sha256:1ebcbde1a53e95b35d8d1e4182cc53537546387e71437b0a7e247c6669062000

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.642624Z digest=sha256:1f4af7050b357a8eb018086c9c054058478a9a0f984d3cf0d23d0ba3ac217146

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)

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.645363Z digest=sha256:a0e227b095ffab9d9ed3763153b3f9ae776ffaa0aaaf2d5257cc83dccde99596

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.647917Z digest=sha256:e7e71669529b36f154799e6a586133e8173d364533aef2847b341700fcad7aee

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)

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.650853Z digest=sha256:89000442b34dac998f93fdd16980fa28ed19bbf109cfc49f7a49e47951085a25

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.653550Z digest=sha256:3bd68a6ab6fabbe3039f0959e7f88e04171bcaa4a6e0422c4d9f6d95fc8bff91

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.655970Z digest=sha256:70bfa5d15ec37c33146aed4f4603713dd6cb97afdc25bf9864aad4617a2354e8

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.658799Z digest=sha256:381c246db0458e1ba9619288de7baa7d0677fdb99f176e377bc7760ffdc0d005

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.661123Z digest=sha256:69f7eb79800a8b106a89985cfd47838e1f681f4b24dea9652fdc241c382da673

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.663615Z digest=sha256:f6e1492bf9f6f0205ff2fa7fd03c2c3f1e3daab4bd4c797327e55a75b35d3923

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)

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.666083Z digest=sha256:a6ba9e46b2955c0e649895460305a9f20494c67a447124f7e659e8d6bc90ae39

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:30.668571Z digest=sha256:4832822356ab7eca93fa709be289de603e95a7efdf603c96f1b070b845ebc82a

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.671401Z digest=sha256:f054a2afb82139fe68e708c59fe3697501ca8e3bfe9adc01a442c46510c2b4b3

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.674324Z digest=sha256:5780a3d92bc827061fec742b33de72c93a698fc35fa4f1f361f084afed7a5bfe

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

Reference 68

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 2026-08-08T06:32:00.761636+00:00.

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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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.679407Z digest=sha256:29658ee53a58af22cedd248707213bab17dfdf93da0571f3c15414c8db913313

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

Reference 70

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:30.682348Z digest=sha256:48522cfa0ba02a257f899fab54a14f13f2166608bea980db2671278ed04ca1bb

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

Reference 71

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.685338Z digest=sha256:e1875938e50edc5d74757186a1e629bdf4afb2b5223c9efd0d4da2015b4e8a98

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)

Reference 72

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.687757Z digest=sha256:d63ca30fec124054b40070afdce449fd5b8fd435bb0473cffcfa632a2869e271

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

Reference 73

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.690643Z digest=sha256:ecf6e742d3dd16c833362c90538ffa015cbc0d60358894ecb790e57141d45162

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

Reference 74

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.693167Z digest=sha256:56e3ae60d7ff022aec1c97686af371948590be3304697ad399c020d04a5b2392

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.

source=pdf_text observed=2026-08-06T15:27:30.695841Z digest=sha256:ea8d2dfd7618cd12c96b1df7fcfca86d183bc5117f0beb9d946e3b279948d47d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.699077Z digest=sha256:9ceb96d9fb9a86684cf9031a4cb39d5c99643faa454e537cbc19774bf99a3450

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.

source=pdf_text observed=2026-08-06T15:27:30.701756Z digest=sha256:e2f2ac429fea3d41bfee610580a88a9558fdeb3e746d88f961a8c7ea35086b1b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.704615Z digest=sha256:bfaab2e10147dc50822c3b13ae8db584b1a61da541c9489e3b3e19feb87ae1a5

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

Reference 79

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.707391Z digest=sha256:44231386d2d308ffd7c6b2e11db07be48b92901aad04fa226f85ea1908cadffb

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]

Reference 80

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.710095Z digest=sha256:c1188831e88b39544e97ffee7c6363f68a5acdaad67e1caff8acaa892477695e

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

Reference 81

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.712761Z digest=sha256:36d9c85b3915858a62126923f374fe65a63cc4ae7b7ab9d12a092d9ad6e53024

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)

Reference 82

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:27:30.715167Z digest=sha256:5749a7a4e41a1534bfd1684082fd371c7656506e3af3c6a3770f1d7813b65b99

Pith citing papers

No inbound Pith citation observations are available.