Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:37:04.355381Z
Paper Citation Record · LEDGER
As of 23 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2504.17719.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:37:04.355381Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
29 of 29 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 53d96a5d-0de6-4fe9-bd75-b601c5b6b0e7 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6c10ac79-44e7-4881-b7cc-c3bbc9e88b0d · outbound
Evaluating Uncertainty in Deep Gaussian Processes Understanding Probabilistic Sparse Gaussian Process Approximations
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac70c097-2896-40b5-a021-2f2737154ef3 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Safe exploration in reinforcement learning: Theory and applications in robotics
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9e1be7cd-7550-437b-9f98-46450be9fc10 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Off-policy reinforcement learning with gaussian processes
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6fcef5a4-4336-4956-b565-ab201c335066 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Unresolved cited work
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f44bf5c-7182-4045-9d6d-de0b6c7f8f22 · outbound
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8fa07bbd-821a-42c7-bfc6-919464521351 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Reinforcement learning with gaussian processes
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a75081e0-a642-4a5f-9b41-934339ba3166 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Generalisation in humans and deep neural networks.Advances in neural information processing systems, 31, 2018
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 819404e7-de9a-4a98-ac9c-f62b34c6f6f1 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Sample efficient reinforcement learn- ing with gaussian processes
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f7379468-bcd3-4d1f-9a8d-bb7452c33146 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e313f205-d696-4c76-bbf7-9dc6d85c1b00 · outbound
Evaluating Uncertainty in Deep Gaussian Processes AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7520345-7d08-4520-8f7d-731f8d5ce21d · outbound
Evaluating Uncertainty in Deep Gaussian Processes Scalable Variational Gaussian Process Classification
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 74e3e7f9-7498-4724-aeb2-e997ded1d949 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Adversarial examples are not bugs, they are features.Advances in neural information processing systems, 32, 2019
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e5fdd9e0-e9f6-4590-b77a-f103f288b08f · outbound
Evaluating Uncertainty in Deep Gaussian Processes Deepsigmapointprocesses
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3112e2f0-4730-4340-942d-29694874099a · outbound
Evaluating Uncertainty in Deep Gaussian Processes Reinforcement learning with gaussian process regression using variational free energy
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 804726bf-8f50-4bea-bc7c-58c5824df8b2 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Simple and scal- able predictive uncertainty estimation using deep ensembles
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation dfcfa455-bba9-4a75-9160-1d08fec3f1a4 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Interpretable function approximation with gaussian processes in value-based model-free reinforcement learning
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7a8e5688-cce6-491b-8a3c-6d5f3c6d24f4 · outbound
Evaluating Uncertainty in Deep Gaussian Processes A review of uncertainty for deep reinforcement learn- ing
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a5692034-8cb9-4bc6-b57e-42f4cf530da5 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Murphy.Probabilistic Machine Learning: Advanced Topics
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 968d923b-1f1e-4c53-9e7a-561ed1bbf84b · outbound
Evaluating Uncertainty in Deep Gaussian Processes Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4986098e-db30-4dfe-a9c7-ff530fa6b359 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Evaluating predictive uncertainty challenge
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation bb0a6139-b270-4f88-9d9f-1d9ec779b72b · outbound
Evaluating Uncertainty in Deep Gaussian Processes Physicochemical Properties of Protein Tertiary Structure
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 328aaa76-0f29-47a0-82c6-4f9c554be2c4 · outbound
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 87f9630a-b6b3-445b-bcf8-90c26d87fe80 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Doubly stochastic variational inference for deep gaussian processes
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3bc4230e-2069-4567-afc4-0162df3923ce · outbound
Evaluating Uncertainty in Deep Gaussian Processes Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958, 2014
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf8e4495-3df6-4f84-bac4-8b0fc87924a3 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Variational learning of inducing variables in sparse gaussian processes
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0bb442f9-6da5-48bf-9e00-88918bff1001 · outbound
Evaluating Uncertainty in Deep Gaussian Processes Q-learning.Machine learning, 8:279–292, 1992
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87ce890a-098c-4bb9-a3fc-681762b5ca3b · outbound
Evaluating Uncertainty in Deep Gaussian Processes Unresolved cited work
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e48ce26c-93d2-4986-9d8f-b764b4540a9e · outbound
Evaluating Uncertainty in Deep Gaussian Processes URL https://proceedings.mlr.press/v5/titsias09a.html
Reference 2009
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
No inbound Pith citation observations are available.