Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T10:24:55.683877Z
Paper Citation Record · LEDGER
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy
As of 20 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:1908.11161.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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
Reference resolution
11 of 11 outbound references displayed
- verified exact1
- verified fuzzy6
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8efa5794-5f2d-448f-8fbe-3edf55689e95 · outbound
This paper cites write newline.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy write newline
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:24:55.628239Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45038294-ffb2-49cf-b633-e74cea807f7e · outbound
This paper cites Zhang, J.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Zhang, J
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:24:55.878117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation dc603b99-8671-43a2-a085-d719052973bf · outbound
This paper cites Probabilistic Models with Deep Neural Networks.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Probabilistic Models with Deep Neural Networks
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T10:24:55.761418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e862e244-6034-4e30-8a6b-dd6d4e316000 · outbound
This paper cites an unresolved cited work.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-14T10:24:55.863036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f1e66d79-5ec8-4401-9ddf-2bd55bda7344 · outbound
This paper cites Bingham, J.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Bingham, J
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:24:55.845898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bbb43d2f-a53e-47fa-b809-e9319048b660 · outbound
This paper cites Caba \ n as, A.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Caba \ n as, A
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:24:55.829131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7c052fb7-aee1-4a92-932f-c6e793e0058b · outbound
This paper cites Edward: A library for probabilistic modeling, inference, and criticism.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Edward: A library for probabilistic modeling, inference, and criticism
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:24:55.662167Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d04b9cc-16ad-4185-ac63-ad427ea22cd6 · outbound
This paper cites Salakhutdinov, Learning deep generative models, Annual Review of Statistics and Its Application 2 (2015) 361--385.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Salakhutdinov, Learning deep generative models, Annual Review of Statistics and Its Application 2 (2015) 361--385
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:24:55.812639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a55270aa-ac36-4a5d-bab3-560b55031344 · outbound
This paper cites Ghahramani, Probabilistic machine learning and artificial intelligence, Nature 521 (7553) (2015) 452.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Ghahramani, Probabilistic machine learning and artificial intelligence, Nature 521 (7553) (2015) 452
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:24:55.794898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 6de453c4-84c2-4db9-af77-174cbcc25e57 · outbound
This paper cites Brooks, A.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Brooks, A
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:24:55.777361Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 522354ee-afd8-45ff-8b94-bfefa5be7536 · outbound
This paper cites Tutorial on Variational Autoencoders.
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Tutorial on Variational Autoencoders
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:24:55.683877Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.