Paper Citation Record · LEDGER

Semi-Implicit Graph Variational Auto-Encoders

As of 22 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:1908.07078.

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

pith.paper-citation-record.v1
1908.07078 v4

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:32:32.081178Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

42 of 42 outbound references displayed

verified exact0
verified fuzzy25
unresolved17
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1114f23f-2d72-4053-9fd1-846dfea4db29 · outbound

This paper cites an unresolved cited work.

Semi-Implicit Graph Variational Auto-Encoders Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:32:32.411164Z

Source-reported events for the cited work

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Observation 38d536a2-16e1-4ad2-8a3f-7aa552455071 · outbound

This paper cites Distributed large-scale natural graph factorization.

Semi-Implicit Graph Variational Auto-Encoders Distributed large-scale natural graph factorization

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.402254Z

Source-reported events for the cited work

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Observation 7c90f86e-3707-4a17-ac23-88d59f5cc961 · outbound

This paper cites Mixed membership stochastic blockmodels.

Semi-Implicit Graph Variational Auto-Encoders Mixed membership stochastic blockmodels

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.393793Z

Source-reported events for the cited work

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Observation 440143e9-c668-4019-b63b-7995682c7f5a · outbound

This paper cites Robust negative sam- pling for network embedding.

Semi-Implicit Graph Variational Auto-Encoders Robust negative sam- pling for network embedding

Reference 4

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Source-reported events for the cited work

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Observation 2f6edbf0-82a5-4151-a31f-cfef551f387a · outbound

This paper cites Laplacian eigenmaps and spectral techniques for embedding and clustering.

Semi-Implicit Graph Variational Auto-Encoders Laplacian eigenmaps and spectral techniques for embedding and clustering

Reference 5

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Source-reported events for the cited work

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Observation 58f2f8e4-e140-40dc-bf28-de9854cbca16 · outbound

This paper cites Manifold regularization: A geometric framework for learning from labeled and unlabeled examples.

Semi-Implicit Graph Variational Auto-Encoders Manifold regularization: A geometric framework for learning from labeled and unlabeled examples

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.375327Z

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Observation 155b2d9e-9b2a-4667-b43d-2be03677b16e · outbound

This paper cites Variational relevance vector machines.

Semi-Implicit Graph Variational Auto-Encoders Variational relevance vector machines

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.366958Z

Source-reported events for the cited work

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Observation 191f8495-458d-4a1b-bcf0-276bb2da35ab · outbound

This paper cites Variational inference: A review for statisticians.

Semi-Implicit Graph Variational Auto-Encoders Variational inference: A review for statisticians

Reference 8

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Source-reported events for the cited work

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Observation 9ff743a9-7a36-4f55-991a-822c259f129f · outbound

This paper cites Deep gaussian embedding of graphs: Unsuper- vised inductive learning via ranking.

Semi-Implicit Graph Variational Auto-Encoders Deep gaussian embedding of graphs: Unsuper- vised inductive learning via ranking

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.354635Z

Source-reported events for the cited work

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Observation 985139d6-1fad-4b20-be97-f8d9fbd53981 · outbound

This paper cites Harp: Hierarchical representation learning for networks.

Semi-Implicit Graph Variational Auto-Encoders Harp: Hierarchical representation learning for networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.345550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a7987bf-1f53-437b-a561-0967635a2929 · outbound

This paper cites Hyperspherical Variational Auto-Encoders.

Semi-Implicit Graph Variational Auto-Encoders Hyperspherical Variational Auto-Encoders

Reference 11

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Source-reported events for the cited work

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Observation bb2b85eb-fbc2-40e4-bbee-af2171aa7127 · outbound

This paper cites Pygsp: Graph signal processing in python.

Semi-Implicit Graph Variational Auto-Encoders Pygsp: Graph signal processing in python

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.336304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5308b4a1-d8fb-440c-aae5-f09817fe8ad7 · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral ﬁltering.

Semi-Implicit Graph Variational Auto-Encoders Convolutional neural networks on graphs with fast localized spectral ﬁltering

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.327748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b928bc95-80a0-4688-b418-85bb4053944f · outbound

This paper cites node2vec: Scalable feature learning for networks.

Semi-Implicit Graph Variational Auto-Encoders node2vec: Scalable feature learning for networks

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d940ab1-aca5-4893-bd0f-83478d7f2605 · outbound

This paper cites Inductive representation learning on large graphs.

Semi-Implicit Graph Variational Auto-Encoders Inductive representation learning on large graphs

Reference 15

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Source-reported events for the cited work

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Observation 0db332b5-9c5a-4e0e-95e6-2754f86a5a2c · outbound

This paper cites An in- troduction to variational methods for graphical models.

Semi-Implicit Graph Variational Auto-Encoders An in- troduction to variational methods for graphical models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.310968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5a4c5aa-b321-4785-a639-57c2920ff35c · outbound

This paper cites Improved variational inference with inverse autoregressive ﬂow.

Semi-Implicit Graph Variational Auto-Encoders Improved variational inference with inverse autoregressive ﬂow

Reference 17

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Source-reported events for the cited work

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Observation dc03a7cf-f05f-4ad9-8a3b-c70ef358d649 · outbound

This paper cites Variational Graph Auto-Encoders.

Semi-Implicit Graph Variational Auto-Encoders Variational Graph Auto-Encoders

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7047774-9ff0-4f6f-a473-7f3d3377718d · outbound

This paper cites Semi-supervised classiﬁcation with graph convolutional networks.

Semi-Implicit Graph Variational Auto-Encoders Semi-supervised classiﬁcation with graph convolutional networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T12:32:32.015480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc3a6264-af42-47e2-8eb8-218e5daac103 · outbound

This paper cites Link-based classiﬁcation.

Semi-Implicit Graph Variational Auto-Encoders Link-based classiﬁcation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.293924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 64ee9d61-44d0-4b87-ae5c-50b1366d0772 · outbound

This paper cites Auxiliary deep generative models.

Semi-Implicit Graph Variational Auto-Encoders Auxiliary deep generative models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.285507Z

Source-reported events for the cited work

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Observation f29ea65f-d579-472d-954a-2b3fab75b03e · outbound

This paper cites Finding community structure in networks using the eigenvectors of matrices.

Semi-Implicit Graph Variational Auto-Encoders Finding community structure in networks using the eigenvectors of matrices

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.275897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4c33c345-cd6d-46c8-a43a-70af64e7e20d · outbound

This paper cites Masked autoregressive ﬂow for density estimation.

Semi-Implicit Graph Variational Auto-Encoders Masked autoregressive ﬂow for density estimation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.267121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 52cc4c4c-9db8-4fb5-874a-ee4fb8e71993 · outbound

This paper cites Fluid communities: a competitive, scalable and diverse community detection algorithm.

Semi-Implicit Graph Variational Auto-Encoders Fluid communities: a competitive, scalable and diverse community detection algorithm

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.258952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 104735e8-7aff-4ab5-9e57-919793a879f9 · outbound

This paper cites Deepwalk: Online learning of social repre- sentations.

Semi-Implicit Graph Variational Auto-Encoders Deepwalk: Online learning of social repre- sentations

Reference 25

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Observation 6a91aff3-2da5-4703-853f-2ded9a31070f · outbound

This paper cites Hierarchical variational models.

Semi-Implicit Graph Variational Auto-Encoders Hierarchical variational models

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f547bdd3-2922-4ef6-8334-0250a7b28773 · outbound

This paper cites Variational Inference with Normalizing Flows.

Semi-Implicit Graph Variational Auto-Encoders Variational Inference with Normalizing Flows

Reference 27

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Observation 671827c6-1845-45a7-bafd-63072d3f209f · outbound

This paper cites Collective classiﬁcation in network data.

Semi-Implicit Graph Variational Auto-Encoders Collective classiﬁcation in network data

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.237196Z

Source-reported events for the cited work

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Observation fa0b4454-f2ba-4f78-8087-cc1dadd9225b · outbound

This paper cites Measuring isp topologies with rocketfuel.

Semi-Implicit Graph Variational Auto-Encoders Measuring isp topologies with rocketfuel

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.228285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9481f8e6-8adf-4e19-a79d-0aceda0ff3db · outbound

This paper cites Line: Large- scale information network embedding.

Semi-Implicit Graph Variational Auto-Encoders Line: Large- scale information network embedding

Reference 30

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Observation e2cc9a93-98c5-41f9-b5d0-c25a9532e28e · outbound

This paper cites Leveraging social media networks for classiﬁcation.

Semi-Implicit Graph Variational Auto-Encoders Leveraging social media networks for classiﬁcation

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation afa9d4ee-8d2f-499b-af5c-78bfdbce2391 · outbound

This paper cites Comparative assessment of large-scale data sets of protein–protein interactions.

Semi-Implicit Graph Variational Auto-Encoders Comparative assessment of large-scale data sets of protein–protein interactions

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.205221Z

Source-reported events for the cited work

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Observation 52317f6e-a2cc-4ef2-bbac-091ae2b2cd3f · outbound

This paper cites Graphical models, exponential families, and variational inference.

Semi-Implicit Graph Variational Auto-Encoders Graphical models, exponential families, and variational inference

Reference 33

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Source-reported events for the cited work

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Observation e8178e3e-cf74-4893-91a0-5ee399c87965 · outbound

This paper cites Collective dynamics of small-world networks.

Semi-Implicit Graph Variational Auto-Encoders Collective dynamics of small-world networks

Reference 34

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Observation aa0ccb7e-6f95-4c5e-9e20-9a5a50fd0af6 · outbound

This paper cites Deep learning via semi- supervised embedding.

Semi-Implicit Graph Variational Auto-Encoders Deep learning via semi- supervised embedding

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.176419Z

Source-reported events for the cited work

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Observation c8469370-0531-4a82-be6b-ca8c7d3ca00e · outbound

This paper cites Representation learning on graphs with jumping knowledge networks.

Semi-Implicit Graph Variational Auto-Encoders Representation learning on graphs with jumping knowledge networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.167088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 05964c3d-97ad-4718-ae03-9e21c01aaf0d · outbound

This paper cites How powerful are graph neural networks? In International Conference on Learning Representations, 2019.

Semi-Implicit Graph Variational Auto-Encoders How powerful are graph neural networks? In International Conference on Learning Representations, 2019

Reference 37

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Source-reported events for the cited work

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Observation d7180306-327a-430f-9146-e5aded4f334d · outbound

This paper cites Revisiting Semi-Supervised Learning with Graph Embeddings.

Semi-Implicit Graph Variational Auto-Encoders Revisiting Semi-Supervised Learning with Graph Embeddings

Reference 38

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Source-reported events for the cited work

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Observation aafb2a8e-6c2a-4df1-ba7d-90d171fcb716 · outbound

This paper cites Semi-implicit variational inference.

Semi-Implicit Graph Variational Auto-Encoders Semi-implicit variational inference

Reference 39

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Source-reported events for the cited work

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Observation 46c078c8-b017-40e4-b9be-9943029254be · outbound

This paper cites Link Prediction Based on Graph Neural Networks.

Semi-Implicit Graph Variational Auto-Encoders Link Prediction Based on Graph Neural Networks

Reference 40

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Source-reported events for the cited work

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Observation 8baf4f38-e6dd-45bb-9028-f7af8efaf99c · outbound

This paper cites Inﬁnite edge partition models for overlapping community detection and link prediction.

Semi-Implicit Graph Variational Auto-Encoders Inﬁnite edge partition models for overlapping community detection and link prediction

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.149119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 20b6ecf8-2161-4b02-bd5d-f85896a2fc52 · outbound

This paper cites Semi-supervised learning using gaussian ﬁelds and harmonic functions.

Semi-Implicit Graph Variational Auto-Encoders Semi-supervised learning using gaussian ﬁelds and harmonic functions

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:32:32.140570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.