Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:14:10.426487Z
Paper Citation Record · LEDGER
As of 11 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2501.15573.
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 2026-08-10T14:14:10.426487Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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
36 of 36 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ccdf621b-4efc-49eb-9038-c8fc76855f33 · outbound
Approximate Message Passing for Bayesian Neural Networks Weight Uncertainty in Neural Networks
Reference 1
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Observation 36435264-fac6-4fc9-bc28-e4cc62b85e6d · outbound
Approximate Message Passing for Bayesian Neural Networks End to End Learning for Self-Driving Cars
Reference 2
Source-reported events for the cited work
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Observation 955cc1dd-5864-4811-a7c8-7f06071f212a · outbound
Approximate Message Passing for Bayesian Neural Networks Wide Mean-Field Bayesian Neural Networks Ignore the Data
Reference 3
Source-reported events for the cited work
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Observation 12a38ce9-2df4-473a-89a8-baa6302f50a3 · outbound
Approximate Message Passing for Bayesian Neural Networks Laplace Redux -- Effortless Bayesian Deep Learning
Reference 4
Source-reported events for the cited work
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Observation 6cc686aa-6ef5-4452-89af-bd5542a13c27 · outbound
Approximate Message Passing for Bayesian Neural Networks Assumed density filtering methods for learning bayesian neural networks
Reference 5
Source-reported events for the cited work
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Observation e2d0e61d-707e-4f96-b18a-0b9bb2aea961 · outbound
Approximate Message Passing for Bayesian Neural Networks Practical variational inference for neural networks
Reference 6
Source-reported events for the cited work
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Observation 6c978f17-c4c8-4499-9335-2a3c0349b85b · outbound
Approximate Message Passing for Bayesian Neural Networks Benchmarking uncertainty estimation methods for deep learning with safety-related metrics
Reference 7
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Observation 2b8a910d-3eb9-4e55-bbe3-16cad1721aee · outbound
Approximate Message Passing for Bayesian Neural Networks Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
Reference 8
Source-reported events for the cited work
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Observation d5d9af88-ca2a-418a-8994-4d5311d873b1 · outbound
Approximate Message Passing for Bayesian Neural Networks Loopy belief propagation: Convergence and effects of message errors
Reference 9
Source-reported events for the cited work
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Observation f918146d-e3d2-48e0-b8c1-eb147d9eacfa · outbound
Approximate Message Passing for Bayesian Neural Networks The Bayesian Learning Rule
Reference 10
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Observation 3ce2cf6f-adfb-4401-a587-c178ac8d9e4c · outbound
Approximate Message Passing for Bayesian Neural Networks Bayesian Dark Knowledge
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 2125a081-b8c1-4bf3-9f53-13303ca05ae3 · outbound
Approximate Message Passing for Bayesian Neural Networks Kschischang, B.J
Reference 12
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Unavailable: canonical work link unavailable.
Observation 68ca1d6f-a376-41de-8506-d72d14a50d59 · outbound
Approximate Message Passing for Bayesian Neural Networks On the detrimental effect of invariances in the likelihood for variational inference
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 0faed823-d7ed-4061-bcb6-49f203227531 · outbound
Approximate Message Passing for Bayesian Neural Networks A ConvNet for the 2020s
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c0c5f1ba-7f3c-4395-96bf-ec22d84654b6 · outbound
Approximate Message Passing for Bayesian Neural Networks SGDR: Stochastic Gradient Descent with Warm Restarts
Reference 15
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Unavailable: canonical work link unavailable.
Observation 7085f623-c57c-4ad9-90af-e8f30e731b70 · outbound
Approximate Message Passing for Bayesian Neural Networks Decoupled Weight Decay Regularization
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00ddb07d-9537-4e66-83f3-8c3799208bd7 · outbound
Approximate Message Passing for Bayesian Neural Networks Deep learning via message passing algorithms based on belief propagation
Reference 17
Source-reported events for the cited work
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Observation f82d4cf4-242a-4027-a5d5-3df34e1851c3 · outbound
Approximate Message Passing for Bayesian Neural Networks Unresolved cited work
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 1878489f-23a8-4beb-a98b-aafcd131d7ee · outbound
Approximate Message Passing for Bayesian Neural Networks Eunnet: Efficient un-normalized convolution layer for stable training of deep residual networks without batch normalization layer
Reference 19
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Unavailable: canonical work link unavailable.
Observation bf9b3da2-d0eb-4eec-8369-c0efc28c96d7 · outbound
Approximate Message Passing for Bayesian Neural Networks Practical Deep Learning with Bayesian Principles
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7c74d0b-f0b2-4fd5-9bb6-03c82f758c07 · outbound
Approximate Message Passing for Bayesian Neural Networks Approximate blocked Gibbs sampling for Bayesian neural networks
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation a3519f90-f2f4-4003-8345-be9fecf2315f · outbound
Approximate Message Passing for Bayesian Neural Networks Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05e0434f-218a-4261-84ce-32a27e4ef298 · outbound
Approximate Message Passing for Bayesian Neural Networks SAM 2: Segment Anything in Images and Videos
Reference 23
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Unavailable: canonical work link unavailable.
Observation cccde684-5a3f-4819-b247-562f961edce9 · outbound
Approximate Message Passing for Bayesian Neural Networks Variational Learning is Effective for Large Deep Networks
Reference 24
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Unavailable: canonical work link unavailable.
Observation 2fb408f7-c3d4-445f-925c-184c310530a5 · outbound
Approximate Message Passing for Bayesian Neural Networks Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks
Reference 25
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Unavailable: canonical work link unavailable.
Observation 1ad29808-541a-499b-8f72-ad114c6d5b70 · outbound
Approximate Message Passing for Bayesian Neural Networks Expectation backpropagation: parameter-free training of multilayer neural networks with continuous or discrete weights
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation dfa4d09f-2422-403f-b016-f9071f6a9411 · outbound
Approximate Message Passing for Bayesian Neural Networks Matchbox: Large scale bayesian recommendations
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 686cd43e-a3d8-4133-b22e-b2cb5eac7ee2 · outbound
Approximate Message Passing for Bayesian Neural Networks Attention Is All You Need
Reference 28
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Unavailable: canonical work link unavailable.
Observation 2cb9baf3-b721-4dda-bd33-a083a03220ae · outbound
Approximate Message Passing for Bayesian Neural Networks Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Reference 29
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Unavailable: canonical work link unavailable.
Observation 849abfb7-ca28-4a51-a098-e6bd719f1342 · outbound
Approximate Message Passing for Bayesian Neural Networks A Spectral Condition for Feature Learning
Reference 30
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Unavailable: canonical work link unavailable.
Observation df9a359e-bf46-4fe1-b3ba-bd6536bbe4cd · outbound
Approximate Message Passing for Bayesian Neural Networks Advances in Variational Inference
Reference 31
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Observation 935d67b0-971e-487b-a558-948a640076d3 · outbound
Approximate Message Passing for Bayesian Neural Networks Beyond Recommendations: From Backward to Forward AI Support of Pilots' Decision-Making Process
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation a113aa86-3728-4dd4-8e46-0e5f952d229e · outbound
Approximate Message Passing for Bayesian Neural Networks @esa (Ref
Reference 33
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Unavailable: canonical work link unavailable.
Observation 7ffc499a-967e-4d71-b4cf-67c8a2a419b8 · outbound
Approximate Message Passing for Bayesian Neural Networks Unresolved cited work
Reference 34
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Unavailable: canonical work link unavailable.
Observation e0850478-691b-42aa-84dc-52c61f65e4da · outbound
Approximate Message Passing for Bayesian Neural Networks , " * write output.state after.block = add.period write newline
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 97ebbd7c-e1d3-4fb2-9e6d-44c6678b2dbe · outbound
Approximate Message Passing for Bayesian Neural Networks write newline
Reference 36
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Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.