Paper Citation Record · LEDGER

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks

As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 3 inbound Pith citation observations for arXiv:2505.17308.

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

pith.paper-citation-record.v1
2505.17308 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:55:47.634895Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T06:26:43.277631Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T06:29:49.731943Z

Reference resolution

34 of 34 outbound references displayed

verified exact1
verified fuzzy25
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 396319b8-98cd-4523-a83e-4fa79daa9a4c · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:44.448660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba5f5914-0a38-4af5-8412-33d50a3e9f8b · outbound

This paper cites Scientific machine learning through physics--informed neural networks: W here we are and what’s next.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Scientific machine learning through physics--informed neural networks: W here we are and what’s next

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:51.951560Z

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.

Observation b316d8a8-6cd5-4926-9d50-bfa3f4f9afdb · outbound

This paper cites Physics-informed neural networks ( PINN s) for fluid mechanics: A review.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Physics-informed neural networks ( PINN s) for fluid mechanics: A review

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:51.759726Z

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.

Observation c82ffa02-d00c-4d25-a6e2-b0e4e11125a6 · outbound

This paper cites Physics-informed neural network ( PINN ) evolution and beyond: A systematic literature review and bibliometric analysis.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Physics-informed neural network ( PINN ) evolution and beyond: A systematic literature review and bibliometric analysis

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:51.519541Z

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.

Observation 973ce53e-e989-4397-a540-1be2adce1af9 · outbound

This paper cites Physics-informed neural networks for heat transfer problems.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Physics-informed neural networks for heat transfer problems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:51.295704Z

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.

Observation ae9456a2-9b87-47ae-834c-9b4e6cc343e0 · outbound

This paper cites Bayesian inference in statistical analysis.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Bayesian inference in statistical analysis

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:44.877946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95e45fa0-f071-4041-9a22-40ee8e17b74e · outbound

This paper cites Bayesian learning for neural networks, volume 118.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Bayesian learning for neural networks, volume 118

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:45.009059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f60d0852-9754-48f6-83e2-50233e8e2449 · outbound

This paper cites Hands-on B ayesian neural networks-- A tutorial for deep learning users.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Hands-on B ayesian neural networks-- A tutorial for deep learning users

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:51.146744Z

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.

Observation 7647c68a-0276-40a1-a0f2-57456bee5045 · outbound

This paper cites B- PINN s: B ayesian physics-informed neural networks for forward and inverse PDE problems with noisy data.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks B- PINN s: B ayesian physics-informed neural networks for forward and inverse PDE problems with noisy data

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:51.011809Z

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.

Observation 052d626f-db1c-4990-b22b-7ecb62204d9f · outbound

This paper cites MCMC using H amiltonian dynamics.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks MCMC using H amiltonian dynamics

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.868410Z

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.

Observation be322ea9-af77-44d2-984f-811d59d7ea10 · outbound

This paper cites Practical variational inference for neural networks.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Practical variational inference for neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.720121Z

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.

Observation a5aa15a6-8880-4ea0-ad90-06a316b02587 · outbound

This paper cites Dropout as a B ayesian approximation: R epresenting model uncertainty in deep learning.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Dropout as a B ayesian approximation: R epresenting model uncertainty in deep learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.582144Z

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.

Observation a6c3ca4a-fa31-4bef-97bc-698e69199462 · outbound

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

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:45.596172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78c8f20d-a7ff-488d-b982-bd5d04e43244 · outbound

This paper cites Stein variational gradient descent: A general purpose B ayesian inference algorithm.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Stein variational gradient descent: A general purpose B ayesian inference algorithm

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.455160Z

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.

Observation 4dde4193-e1a5-467b-b77b-c98ff7a4b62c · outbound

This paper cites On linear identifiability of learned representations.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks On linear identifiability of learned representations

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.329175Z

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.

Observation 88680288-aa3f-4ee5-b82a-1fc1d396bead · outbound

This paper cites F unction S pace P article O ptimization for B ayesian N eural N etworks.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks F unction S pace P article O ptimization for B ayesian N eural N etworks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.195896Z

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.

Observation 1d3e36c1-fbac-4986-bdf0-a70a88a3da21 · outbound

This paper cites Repulsive deep ensembles are B ayesian.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Repulsive deep ensembles are B ayesian

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:50.042048Z

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.

Observation e5ff3b39-39a8-4717-bbda-b36efcc3c489 · outbound

This paper cites The variational formulation of the F okker-- P lanck equation.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks The variational formulation of the F okker-- P lanck equation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:49.920299Z

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.

Observation 9675b18b-adad-4ca8-97aa-12fdf178c537 · outbound

This paper cites B ayesian neural network and B ayesian physics-informed neural network via variational inference for seismic petrophysical inversion.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks B ayesian neural network and B ayesian physics-informed neural network via variational inference for seismic petrophysical inversion

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:49.807665Z

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.

Observation 6e7ae471-2a1f-46d4-afca-03f23bbe4459 · outbound

This paper cites Practical uncertainty quantification for space-dependent inverse heat conduction problem via ensemble physics-informed neural networks.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Practical uncertainty quantification for space-dependent inverse heat conduction problem via ensemble physics-informed neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:49.683902Z

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.

Observation 4dcd93a5-4959-4bf1-9cf9-9e069ca2bf5c · outbound

This paper cites Physics-informed neural networks for cardiac activation mapping.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Physics-informed neural networks for cardiac activation mapping

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:49.510914Z

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.

Observation 19b4ef2a-0c5f-4ee6-b452-f5c3cc12d684 · outbound

This paper cites Improved training of physics-informed neural networks with model ensembles.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Improved training of physics-informed neural networks with model ensembles

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:49.328305Z

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.

Observation 16c3f96a-8df3-4c14-aa30-6fc0a7c59af8 · outbound

This paper cites Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:46.467626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f779811-d0c0-4938-9d97-c5ec71e28db3 · outbound

This paper cites Ensemble learning for Physics Informed Neural Networks: a Gradient Boosting approach.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Ensemble learning for Physics Informed Neural Networks: a Gradient Boosting approach

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:46.558047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7999c6b-a97b-4756-8acf-cf40a3bad51f · outbound

This paper cites Multi-output physics-informed neural networks for forward and inverse PDE problems with uncertainties.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Multi-output physics-informed neural networks for forward and inverse PDE problems with uncertainties

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:49.139076Z

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.

Observation 69648ba3-7b91-4d49-8173-c9b8c4082114 · outbound

This paper cites Evidential Physics-Informed Neural Networks.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Evidential Physics-Informed Neural Networks

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:55:47.898636Z

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.

Observation c5d621ca-45c3-4635-b902-23b57f5e613c · outbound

This paper cites o ver, Bj \.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks o ver, Bj \

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:48.949826Z

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.

Observation 4e5ca425-c0ca-4448-9d0c-fb83aebabde7 · outbound

This paper cites Gradient flows: in metric spaces and in the space of probability measures.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Gradient flows: in metric spaces and in the space of probability measures

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:47.017091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea4f4969-0aed-4824-a68f-bc9d81e6d29f · outbound

This paper cites Pdebench: A n extensive benchmark for scientific machine learning.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Pdebench: A n extensive benchmark for scientific machine learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:48.741869Z

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.

Observation 17566e7e-0cd3-4e16-adfa-5d0b758b0368 · outbound

This paper cites Physics-informed neural networks with unknown measurement noise.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Physics-informed neural networks with unknown measurement noise

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:48.572225Z

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.

Observation 82478e9a-cf7f-4acc-a04c-0570ccbf5655 · outbound

This paper cites Input-gradient space particle inference for neural network ensembles.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Input-gradient space particle inference for neural network ensembles

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:48.440524Z

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.

Observation f90d92a1-552d-458d-901a-5d2dca4bcd92 · outbound

This paper cites Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, and Noah D.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, and Noah D

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:48.267765Z

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.

Observation a93d7a56-58b3-4e30-b736-4b3444e166de · outbound

This paper cites The No-U-Turn sampler: adaptively setting path lengths in H amiltonian M onte C arlo.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks The No-U-Turn sampler: adaptively setting path lengths in H amiltonian M onte C arlo

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:48.079194Z

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.

Observation 3147164e-5d70-4518-a900-7d7659f6506d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Adam: A Method for Stochastic Optimization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:47.634895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ff70efa2-5ee4-4c2f-9f84-fbb4ee0b4c97 · inbound

Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles cites this paper.

Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:21:26.808735Z

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.

Observation 6ccc0e40-c50d-4c6a-b23f-25c3179e4b87 · inbound

Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks cites this paper.

Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:45:56.872490Z

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.

Observation e7febe1e-f88a-4c28-a850-f396de7fcadd · inbound

Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks cites this paper.

Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:29:49.735583Z

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.