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Paper Citation Record · LEDGER

Wavelet-based Variational Autoencoders for High-Resolution Image Generation

As of 22 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2504.13214.

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

pith.paper-citation-record.v1
2504.13214 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:29.821968Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

28 of 28 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bcdca62b-4a5b-4878-a30c-b7c7efae0ba5 · outbound

This paper cites Bowman, Luke Vilnis, Oriol Vinyals, Andrew M.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Bowman, Luke Vilnis, Oriol Vinyals, Andrew M

Reference 1

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Observation ec90fcd9-498d-41e3-a1da-351efffed1d1 · outbound

This paper cites Importance-weighted autoencoders.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Importance-weighted autoencoders

Reference 2

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Observation 85e88a8e-ab98-407b-a975-b3c724a17320 · outbound

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Wavelet-based Variational Autoencoders for High-Resolution Image Generation Unresolved cited work

Reference 3

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Observation 20300029-e00f-4319-aef3-d246641c838f · outbound

This paper cites Very deep vaes generalize autoregressive models and can outperform them on im- ages.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Very deep vaes generalize autoregressive models and can outperform them on im- ages

Reference 4

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Observation 8ace1c4d-0aab-4e87-b2f8-e04925441529 · outbound

This paper cites Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus

Reference 5

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Source-reported events for the cited work

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Observation 4ef2c12c-3f82-477a-93a9-d21574ae2c5d · outbound

This paper cites Multi-Anchor Active Domain Adaptation for Semantic Segmentation.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Multi-Anchor Active Domain Adaptation for Semantic Segmentation

Reference 6

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Observation bfb0f90b-91ab-4b49-8c66-2fd6b91a7cd0 · outbound

This paper cites Generative adversarial nets.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Generative adversarial nets

Reference 7

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Source-reported events for the cited work

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Observation b6a5d0de-1fbc-4da3-9ec7-60b7490fcc60 · outbound

This paper cites Draw: A recurrent neural network for image generation.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Draw: A recurrent neural network for image generation

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2a12439d-a633-4c56-9212-7f596a268064 · outbound

This paper cites Pixelvae: A latent variable model for natural images.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Pixelvae: A latent variable model for natural images

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 37928a9f-c880-4ba3-85d9-52169f424560 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 10

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Source-reported events for the cited work

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Observation 10975b56-e28e-4b7f-8262-c58741eb365d · outbound

This paper cites Progressive growing of gans for improved quality, stability, and variation.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Progressive growing of gans for improved quality, stability, and variation

Reference 11

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Observation 1ef84368-9dab-4d51-8219-479005f642be · outbound

This paper cites An introduction to variational methods for graphical models.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation An introduction to variational methods for graphical models

Reference 12

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Source-reported events for the cited work

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Observation c05971b3-66f4-439c-8e2d-2f5490054513 · outbound

This paper cites Kingma, Tim Salimans, and Max Welling.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Kingma, Tim Salimans, and Max Welling

Reference 13

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Observation 722ee557-002c-4a09-acd5-1ca660d9fefe · outbound

This paper cites Kingma and Max Welling.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Kingma and Max Welling

Reference 14

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Source-reported events for the cited work

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Observation 7f1a0700-5c9e-462d-a097-c51221aae936 · outbound

This paper cites A Hybrid Wavelet-Fourier Method for Next-Generation Conditional Diffusion Models.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation A Hybrid Wavelet-Fourier Method for Next-Generation Conditional Diffusion Models

Reference 16

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Source-reported events for the cited work

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Observation d2844755-ca01-4d6c-9757-0264ca3b4844 · outbound

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Wavelet-based Variational Autoencoders for High-Resolution Image Generation Unresolved cited work

Reference 17

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Source-reported events for the cited work

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Observation ded80090-d17e-4d41-ab34-9011a54240d2 · outbound

This paper cites Kulkarni, William F.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Kulkarni, William F

Reference 18

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Source-reported events for the cited work

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Observation 75096b1c-66a3-405d-9925-0129c75e4d14 · outbound

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Wavelet-based Variational Autoencoders for High-Resolution Image Generation Unresolved cited work

Reference 19

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Observation 95f3aee1-c72e-4619-91d3-0052b673dac6 · outbound

This paper cites A wavelet tour of signal processing.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation A wavelet tour of signal processing

Reference 20

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Source-reported events for the cited work

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Observation 3d17ab97-3297-4047-9a7b-b7958006678b · outbound

This paper cites Patil and S.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Patil and S

Reference 21

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Source-reported events for the cited work

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Observation edc47333-0500-4a7d-94df-8d5b05cc8502 · outbound

This paper cites Generating diverse high-fidelity images with vq-vae-2.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Generating diverse high-fidelity images with vq-vae-2

Reference 22

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Source-reported events for the cited work

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Observation 229e82c3-907c-46fa-a79f-38c3ef731bad · outbound

This paper cites Variational inference with normalizing flows.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Variational inference with normalizing flows

Reference 23

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Source-reported events for the cited work

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Observation 5be2af1c-bf5b-4261-adfe-fd339e079573 · outbound

This paper cites Stochastic backpropagation and approximate inference in deep generative models.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Stochastic backpropagation and approximate inference in deep generative models

Reference 24

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Source-reported events for the cited work

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Observation a3cd1464-ff9f-4443-a8f5-55f6687f585c · outbound

This paper cites Ladder varia- tional autoencoders.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Ladder varia- tional autoencoders

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3b814a4e-e110-4373-b527-ef258a2d49e4 · outbound

This paper cites Tomczak and Max Welling.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Tomczak and Max Welling

Reference 26

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Source-reported events for the cited work

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Observation 4ffbb8af-477f-4e1c-b210-cc7ae304725a · outbound

This paper cites Nvae: A deep hierarchical variational autoencoder.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Nvae: A deep hierarchical variational autoencoder

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f9235bb6-c912-4fdb-baa9-162565c469e5 · outbound

This paper cites Bovik, Hamid R.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Bovik, Hamid R

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 303ad481-13c2-4582-8837-bb6849ece28e · outbound

This paper cites Attribute2image: Conditional image generation from visual attributes.

Wavelet-based Variational Autoencoders for High-Resolution Image Generation Attribute2image: Conditional image generation from visual attributes

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.