Paper Citation Record · LEDGER

Density estimation in representation space to predict model uncertainty

As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:1908.07235.

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

pith.paper-citation-record.v1
1908.07235 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:25:48.507194Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy6
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 50573c5a-d27c-46a2-b6b0-3a0eaccaa4b9 · outbound

This paper cites Concrete Problems in AI Safety.

Density estimation in representation space to predict model uncertainty Concrete Problems in AI Safety

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.353988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29d27c3f-0078-40cc-a837-39b32378faf8 · outbound

This paper cites Synthesizing Robust Adversarial Examples.

Density estimation in representation space to predict model uncertainty Synthesizing Robust Adversarial Examples

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.359575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06739f99-d675-4c41-8498-2756e0090a56 · outbound

This paper cites Learning Confidence for Out-of-Distribution Detection in Neural Networks.

Density estimation in representation space to predict model uncertainty Learning Confidence for Out-of-Distribution Detection in Neural Networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.364649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4551c657-727c-4e52-9829-e1e427d1144e · outbound

This paper cites Detecting Adversarial Samples from Artifacts.

Density estimation in representation space to predict model uncertainty Detecting Adversarial Samples from Artifacts

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.370065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11697c3a-a43b-4783-aaaf-fcf596f32b50 · outbound

This paper cites Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning.

Density estimation in representation space to predict model uncertainty Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.375495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bca10cb-8b8a-4ac3-97de-2266585eb916 · outbound

This paper cites Conditional Neural Processes.

Density estimation in representation space to predict model uncertainty Conditional Neural Processes

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.380791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3573f5ea-398b-4d77-b925-9bcb5af7aaa3 · outbound

This paper cites On Calibration of Modern Neural Networks.

Density estimation in representation space to predict model uncertainty On Calibration of Modern Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.386540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 218204a0-b82a-4154-a03f-4b9734854546 · outbound

This paper cites Noise Contrastive Priors for Functional Uncertainty.

Density estimation in representation space to predict model uncertainty Noise Contrastive Priors for Functional Uncertainty

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.391422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc187e0d-95d6-460b-8a6f-d635b9084b2c · outbound

This paper cites Cautious Deep Learning.

Density estimation in representation space to predict model uncertainty Cautious Deep Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.396402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2929d2bf-4900-4cab-9ae4-ff8e901d28db · outbound

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

Density estimation in representation space to predict model uncertainty Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.401415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 893f9fc7-be3d-475d-8e7b-db7caffa5e2a · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Density estimation in representation space to predict model uncertainty A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.406185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc834ae8-cd89-438e-b625-ce0e78038a8c · outbound

This paper cites Adversarial Attacks on Neural Network Policies.

Density estimation in representation space to predict model uncertainty Adversarial Attacks on Neural Network Policies

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:25:49.054549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 70f81c6c-3ebd-453b-8438-fa0b67906b1c · outbound

This paper cites To Trust Or Not To Trust A Classifier.

Density estimation in representation space to predict model uncertainty To Trust Or Not To Trust A Classifier

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T12:25:48.721111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5d121341-ea24-4082-ade2-af6d3d5bd8b5 · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural networks.

Density estimation in representation space to predict model uncertainty Imagenet classiﬁcation with deep convolutional neural networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.421062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b941225-1a46-4612-a604-33ceacc05b50 · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Density estimation in representation space to predict model uncertainty Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.425515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf457e21-c82b-4998-94e0-9c93db6559cf · outbound

This paper cites Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples.

Density estimation in representation space to predict model uncertainty Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.430239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd20fe0f-6048-4b31-96a1-cd1841c4842e · outbound

This paper cites A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks.

Density estimation in representation space to predict model uncertainty A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.435367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 466cf5a4-a635-4b92-a765-1cf3bb11e0cf · outbound

This paper cites Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks.

Density estimation in representation space to predict model uncertainty Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.440135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7e8c525-2735-4402-8b2e-6d6278fc659b · outbound

This paper cites Predictive uncertainty estimation via prior networks.

Density estimation in representation space to predict model uncertainty Predictive uncertainty estimation via prior networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:25:49.015274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1f90fcfe-582a-4b1b-a228-1f7605f9a889 · outbound

This paper cites Do Deep Generative Models Know What They Don't Know?.

Density estimation in representation space to predict model uncertainty Do Deep Generative Models Know What They Don't Know?

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.449564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 148f44fc-2117-4478-b536-d761572546da · outbound

This paper cites an unresolved cited work.

Density estimation in representation space to predict model uncertainty Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:25:48.999157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 723d866a-d6bc-41dc-9a98-fd8bc13d4b30 · outbound

This paper cites Deep Neural Networks are Easily Fooled: High Conﬁdence Predictions for Unrecognizable Images.

Density estimation in representation space to predict model uncertainty Deep Neural Networks are Easily Fooled: High Conﬁdence Predictions for Unrecognizable Images

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:25:48.982280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5d74092b-d117-48ea-bda8-d28ea15d522a · outbound

This paper cites Classification Uncertainty of Deep Neural Networks Based on Gradient Information.

Density estimation in representation space to predict model uncertainty Classification Uncertainty of Deep Neural Networks Based on Gradient Information

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:25:48.634322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 788a3d0b-ca6e-46c8-a1f7-8ca721d6b06d · outbound

This paper cites Randomized Prior Functions for Deep Reinforcement Learning.

Density estimation in representation space to predict model uncertainty Randomized Prior Functions for Deep Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.468296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3436dad-647b-460a-95ca-3202c3b3c916 · outbound

This paper cites Deep k-Nearest Neighbors: Towards Conﬁdent, Interpretable and Robust Deep Learning.

Density estimation in representation space to predict model uncertainty Deep k-Nearest Neighbors: Towards Conﬁdent, Interpretable and Robust Deep Learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:25:48.966007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation de9aadba-2a74-45fc-8973-55aea3623196 · outbound

This paper cites Do ImageNet Classifiers Generalize to ImageNet?.

Density estimation in representation space to predict model uncertainty Do ImageNet Classifiers Generalize to ImageNet?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.477109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b3b037b-bf29-4057-b421-fd5c252882a3 · outbound

This paper cites Berg, and Li Fei-Fei.

Density estimation in representation space to predict model uncertainty Berg, and Li Fei-Fei

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.482072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d760329a-7707-43ae-85a2-f80a58349283 · outbound

This paper cites Evidential deep learning to quantify classiﬁcation uncertainty.

Density estimation in representation space to predict model uncertainty Evidential deep learning to quantify classiﬁcation uncertainty

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:25:48.939258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e73a04e4-6777-46c8-9c8f-58711f949089 · outbound

This paper cites Prototypical Networks for Few-shot Learning.

Density estimation in representation space to predict model uncertainty Prototypical Networks for Few-shot Learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.491783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3085aa5-056d-4364-9ac5-687dcb943c8f · outbound

This paper cites Inception-v4, Inception- ResNet and the Impact of Residual Connections on Learning.

Density estimation in representation space to predict model uncertainty Inception-v4, Inception- ResNet and the Impact of Residual Connections on Learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:25:48.923582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 290c5cf4-68ba-456f-9787-7d9ba520f866 · outbound

This paper cites Adversarial Risk and the Dangers of Evaluating Against Weak Attacks.

Density estimation in representation space to predict model uncertainty Adversarial Risk and the Dangers of Evaluating Against Weak Attacks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.502540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f413e7a3-02b5-4185-a5e0-2958e3e527f1 · outbound

This paper cites Deep Sets.

Density estimation in representation space to predict model uncertainty Deep Sets

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T12:25:48.507194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.