Paper Citation Record · LEDGER

Tractable Representation Learning with Probabilistic Circuits

As of 7 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2507.04385.

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

pith.paper-citation-record.v1
2507.04385 v2

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:54:23.106538Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

20 of 20 outbound references displayed

verified exact4
verified fuzzy7
unresolved7
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c948597d-30e1-4d07-9243-2f80584b544a · outbound

This paper cites This comparison highlights the flexibility of APCs compared to the prior autoencoding scheme introduced in Vergari et al.

Tractable Representation Learning with Probabilistic Circuits This comparison highlights the flexibility of APCs compared to the prior autoencoding scheme introduced in Vergari et al

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:24.303569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0024cdda-cfcd-4a54-a6dd-8d1c5f4263f2 · outbound

This paper cites C.4 Additional Reconstruction Visualizations To provide further visual insights and extend the quantitative reconstructions presented in Fig.

Tractable Representation Learning with Probabilistic Circuits C.4 Additional Reconstruction Visualizations To provide further visual insights and extend the quantitative reconstructions presented in Fig

Reference 5

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T19:54:24.703875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ad791225-0fc5-49b4-b567-1b7350c41a37 · outbound

This paper cites Decoupled Weight Decay Regularization.

Tractable Representation Learning with Probabilistic Circuits Decoupled Weight Decay Regularization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:21.843711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcb80fcb-d80f-4907-930d-08e9d606e518 · outbound

This paper cites Full Evidence: APCs are successfully distilling the knowledge from their teacher.

Tractable Representation Learning with Probabilistic Circuits Full Evidence: APCs are successfully distilling the knowledge from their teacher

Reference 8

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T19:54:24.213385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 73e08c52-20b4-453b-9074-dbac3c88acd7 · outbound

This paper cites Distilling Task-Specific Knowledge from BERT into Simple Neural Networks.

Tractable Representation Learning with Probabilistic Circuits Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:22.245575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40a36fc3-6fa7-4e2d-b58b-1d483e383ad1 · outbound

This paper cites Autoencoders and Probabilistic Inference with Missing Data: An Exact Solution for The Factor Analysis Case.

Tractable Representation Learning with Probabilistic Circuits Autoencoders and Probabilistic Inference with Missing Data: An Exact Solution for The Factor Analysis Case

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:54:23.359391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 169de85b-3d75-4f7f-8fb6-e0e41d90a3e0 · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

Tractable Representation Learning with Probabilistic Circuits LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:22.538615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 294f066e-14d8-4891-a894-92b7e83ff5f9 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

Tractable Representation Learning with Probabilistic Circuits DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:22.601019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1379fca-118f-4860-976f-e2b0c5a389eb · outbound

This paper cites Our implementation is available as open-source software athttps: //github.com/placeholder-url.

Tractable Representation Learning with Probabilistic Circuits Our implementation is available as open-source software athttps: //github.com/placeholder-url

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:25.106557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1e8a097b-d38c-4ed9-9042-d52befaf3dbb · outbound

This paper cites convolutional.

Tractable Representation Learning with Probabilistic Circuits convolutional

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:24.910794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation be8ab835-3ae5-4dbe-ba67-7ebf6e8bbe66 · outbound

This paper cites an unresolved cited work.

Tractable Representation Learning with Probabilistic Circuits Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:54:24.487793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c940f089-b709-429f-a25c-7b6c9cbfae40 · outbound

This paper cites not-miwae: Deep generative modelling with missing not at random data.

Tractable Representation Learning with Probabilistic Circuits not-miwae: Deep generative modelling with missing not at random data

Reference 2006

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:26.040335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99cedca0-0a6e-4d5e-8a96-00c7bd52a4a5 · outbound

This paper cites Learning invariant features through local space contraction.

Tractable Representation Learning with Probabilistic Circuits Learning invariant features through local space contraction

Reference 2014

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:54:23.571366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dedeb374-758d-4c71-ba87-dc2794a790db · outbound

This paper cites 22 Lili Mou, Ran Jia, Yan Xu, Ge Li, Lu Zhang, and Zhi Jin.

Tractable Representation Learning with Probabilistic Circuits 22 Lili Mou, Ran Jia, Yan Xu, Ge Li, Lu Zhang, and Zhi Jin

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:25.344066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a4d4a62-e8e9-4069-8005-b61ac9387c40 · outbound

This paper cites Learning markov network structure with decision trees.2010 IEEE International Conference on Data Mining,.

Tractable Representation Learning with Probabilistic Circuits Learning markov network structure with decision trees.2010 IEEE International Conference on Data Mining,

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:25.518411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d08ff380-3b03-490a-84ee-3e880c888ceb · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Tractable Representation Learning with Probabilistic Circuits Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:22.416141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1960aaf-e50d-4481-9635-ba524d44ce1a · outbound

This paper cites Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images.

Tractable Representation Learning with Probabilistic Circuits Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:21.024377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d636746-cc97-4558-bac4-4e80a720b562 · outbound

This paper cites mDAE : modified Denoising AutoEncoder for missing data imputation.

Tractable Representation Learning with Probabilistic Circuits mDAE : modified Denoising AutoEncoder for missing data imputation

Reference 2020

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:54:24.040768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cf825e0e-0c83-418f-94e9-9df954eb0c6c · outbound

This paper cites Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks.

Tractable Representation Learning with Probabilistic Circuits Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:54:23.790024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3b485c4a-e711-48ca-b7d7-224ee9a3eb5b · outbound

This paper cites Grammar variational autoencoder.

Tractable Representation Learning with Probabilistic Circuits Grammar variational autoencoder

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:54:25.758902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.