Paper Citation Record · LEDGER

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders

As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2507.17255.

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

pith.paper-citation-record.v1
2507.17255 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:59:15.786215Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

31 of 31 outbound references displayed

verified exact4
verified fuzzy3
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e7d25bdf-5c6a-47c6-bca6-b114b627a773 · outbound

This paper cites Deep generative clustering with vaes and expectation- maximization.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Deep generative clustering with vaes and expectation- maximization

Reference 1

Resolution: verified exact; raw_fallback, observed 2026-08-06T14:59:19.025952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 209350a0-afe7-4fd7-bacd-178dfd3176df · outbound

This paper cites Constraining Variational Inference with Geometric Jensen-Shannon Divergence.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Constraining Variational Inference with Geometric Jensen-Shannon Divergence

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:59:17.800381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f7fe6842-113a-4d3d-8e4e-b9918dbca83e · outbound

This paper cites Generative Adversarial Networks.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Generative Adversarial Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:11.972261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a01fc68-6970-4008-bab2-405187ab5149 · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:12.328504Z

Source-reported events for the cited work

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Observation 0e1a1b5f-effa-4eae-8f88-4aca322f11c8 · outbound

This paper cites A Style-Based Generator Architecture for Generative Adversarial Networks.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders A Style-Based Generator Architecture for Generative Adversarial Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:12.484510Z

Source-reported events for the cited work

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Observation ee741500-13b7-41ff-9bdc-c717ae09ef4d · outbound

This paper cites Semantic Interpolation in Implicit Models.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Semantic Interpolation in Implicit Models

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:59:17.400345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e4e6bf33-a9b2-4795-9d80-353197e8a85e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Adam: A Method for Stochastic Optimization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:12.871859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb9f406a-738d-4483-b38b-3fb792288b26 · outbound

This paper cites Auto-Encoding Variational Bayes.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Auto-Encoding Variational Bayes

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:13.083977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7ee8144-ef5b-4383-b129-ac0b43f644d3 · outbound

This paper cites Exploring the Latent Space of Autoencoders with Interventional Assays.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Exploring the Latent Space of Autoencoders with Interventional Assays

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T14:59:17.064876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 874e4d48-4de1-43c7-a337-ea605be27001 · outbound

This paper cites Adversarial Autoencoders.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Adversarial Autoencoders

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:13.689930Z

Source-reported events for the cited work

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Observation ab3ca5eb-6e39-442f-88f9-d05ddc812e4a · outbound

This paper cites Learning sparse generative models of audiovisual signals.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Learning sparse generative models of audiovisual signals

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:59:20.062513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bb47a5bf-4766-4d94-9c6c-71740d6ad146 · outbound

This paper cites Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T14:59:16.715699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 99966cc8-5299-4cb0-b59f-3e82ba28b61a · outbound

This paper cites Wasserstein Auto-Encoders.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Wasserstein Auto-Encoders

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:14.375337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e56f0166-8947-4c9e-889f-995b31267123 · outbound

This paper cites Neural Discrete Representation Learning.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Neural Discrete Representation Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:14.693214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5681e4e3-dab0-4eed-b458-7fd6a3d5da60 · outbound

This paper cites Learning Manifold Dimensions with Conditional Variational Autoencoders.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Learning Manifold Dimensions with Conditional Variational Autoencoders

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:59:16.091618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b036b0a5-42bb-49b4-a791-4c83a1f54ec8 · outbound

This paper cites [2019, 2018] This section will further explore and validate the generative potential of AEs from this perspective.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders [2019, 2018] This section will further explore and validate the generative potential of AEs from this perspective

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:59:19.501569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e9f4dfea-c903-4254-b76e-a1351e1e86f5 · outbound

This paper cites Extending the Geometric View: Connection to VQ-V AE.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Extending the Geometric View: Connection to VQ-V AE

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:59:19.168962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d1beb177-339c-4da9-aa6a-78ac0ca209ab · outbound

This paper cites an unresolved cited work.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-06T14:59:19.840828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7aa49434-2137-458e-bcae-be383d8191b6 · outbound

This paper cites URL https://doi.org/10.1038/323533a0.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders URL https://doi.org/10.1038/323533a0

Reference 1986

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:14.086648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4434e2c4-4f87-4ec1-9ba1-a187ea9eea5a · outbound

This paper cites Dependent censoring based on copulas.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Dependent censoring based on copulas

Reference 2008

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T14:59:16.438225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a5b43734-4ceb-40f2-a5fc-ae8674b8185b · outbound

This paper cites Neural networks and principal component analysis: Learning from examples without local minima.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Neural networks and principal component analysis: Learning from examples without local minima

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:11.137414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3992d189-460c-43c1-b653-a6ac86aecff7 · outbound

This paper cites Preventing Posterior Collapse with delta-VAEs.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Preventing Posterior Collapse with delta-VAEs

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:13.490988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c673f06-683f-4ef2-ba04-c1dda56c7e30 · outbound

This paper cites Sampling Generative Networks.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Sampling Generative Networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:14.948033Z

Source-reported events for the cited work

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Observation 838561a6-9db6-424a-95c4-5d5f1f9e8794 · outbound

This paper cites Understanding disentangling in $\beta$-VAE.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Understanding disentangling in $\beta$-VAE

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:12.143445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3915d53-b967-4b15-9f12-7d5e7eb442b8 · outbound

This paper cites Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:11.458314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d39a0b7-0b9e-40ed-a4f1-aea90672fcd3 · outbound

This paper cites Generalized Denoising Auto-Encoders as Generative Models.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Generalized Denoising Auto-Encoders as Generative Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:11.305209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9081bd48-bf2f-498b-ae5d-41044e043284 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:13.832982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7443794-de01-4177-9916-1a96d5f097c7 · outbound

This paper cites Variational Autoencoder with Learned Latent Structure.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Variational Autoencoder with Learned Latent Structure

Reference 2021

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T14:59:18.192441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1759e0d8-4e96-4be6-bea9-459187ea03f9 · outbound

This paper cites Towards Better Data Augmentation using Wasserstein Distance in Variational Auto-encoder.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders Towards Better Data Augmentation using Wasserstein Distance in Variational Auto-encoder

Reference 2022

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T14:59:18.505366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dca1049b-79fb-4a6f-97de-ec9e6462f0f9 · outbound

This paper cites A Geometric Perspective on Autoencoders.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders A Geometric Perspective on Autoencoders

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:13.251020Z

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Unavailable: canonical work link unavailable.

Observation 7614c876-ae3f-4abe-b68e-31c0ef039c9f · outbound

This paper cites doi: https://doi.org/10.1016/j.patcog.2025.111500.

From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders doi: https://doi.org/10.1016/j.patcog.2025.111500

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:15.101369Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.