Paper Citation Record · LEDGER

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

As of 10 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 3 inbound Pith citation observations for arXiv:2502.06525.

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

pith.paper-citation-record.v1
2502.06525 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:18:23.289717Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:09:06.138004Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-29T11:23:21.270502Z

Reference resolution

49 of 49 outbound references displayed

verified exact2
verified fuzzy36
unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 55b4ace7-b0bc-4567-b07d-f28d33d31007 · outbound

This paper cites write newline.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis write newline

Reference 1

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Source-reported events for the cited work

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Observation f1aad82b-6ef8-42e4-b121-e685cdc2329e · outbound

This paper cites Gradient flows: in metric spaces and in the space of probability measures.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Gradient flows: in metric spaces and in the space of probability measures

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T15:18:22.132350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a3e6e16-e281-4dfa-b882-e684bd0a6d72 · outbound

This paper cites W asserstein generative adversarial networks.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis W asserstein generative adversarial networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.241186Z

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Observation 8fb7248f-b8ed-4078-9242-c4fc74675388 · outbound

This paper cites A., Pantazis, Y., and Rey-Bellet, L.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis A., Pantazis, Y., and Rey-Bellet, L

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.226306Z

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Observation ef9f4889-6d4c-46ef-a5bb-b3c939cfeb53 · outbound

This paper cites M., Kucukelbir, A., and McAuliffe, J.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis M., Kucukelbir, A., and McAuliffe, J

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.212619Z

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Observation c427fdaa-1f7a-4a41-ac04-e4f4fe942c55 · outbound

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Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Unresolved cited work

Reference 6

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Source-reported events for the cited work

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Observation 89f491c0-4e48-4d09-9acb-044274cf51bf · outbound

This paper cites Sliced and radon wasserstein barycenters of measures.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Sliced and radon wasserstein barycenters of measures

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.120947Z

Source-reported events for the cited work

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Observation 8b67b4fb-ecca-4801-845a-e7fbf46d86e8 · outbound

This paper cites Unidimensional and evolution methods for optimal transportation.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Unidimensional and evolution methods for optimal transportation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.046177Z

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Observation 687df47b-4d82-48fe-9d75-c2c457fae25e · outbound

This paper cites P., Kok, P.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis P., Kok, P

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.028344Z

Source-reported events for the cited work

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Observation bd8f0b5b-22a4-4ac0-8f5b-1cf0b27c4b76 · outbound

This paper cites EigenVI: score-based variational inference with orthogonal function expansions.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis EigenVI: score-based variational inference with orthogonal function expansions

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:26.012332Z

Source-reported events for the cited work

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Observation f23bb420-8d9d-4ee4-936a-fdb663dd2ee7 · outbound

This paper cites C., Gower, R.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis C., Gower, R

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.992933Z

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Observation f58ebff4-bcf3-411c-b7d9-de96287c87c7 · outbound

This paper cites and Bach, F.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis and Bach, F

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.960935Z

Source-reported events for the cited work

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Observation f4a38907-084f-4907-9870-964a79ca92cf · outbound

This paper cites Scalable wasserstein gradient flow for generative modeling through unbalanced optimal transport.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Scalable wasserstein gradient flow for generative modeling through unbalanced optimal transport

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.808058Z

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Observation 3ac27ab4-fcf1-4e33-880c-60ad59134bb0 · outbound

This paper cites and Santambrogio, F.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis and Santambrogio, F

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.675657Z

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Observation b3848af9-42c8-49d9-9d4d-3f70b668984b · outbound

This paper cites and Seljak, U.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis and Seljak, U

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.658068Z

Source-reported events for the cited work

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Observation ffa3e387-3ed2-4373-8bd4-ad7de3389698 · outbound

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Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Unresolved cited work

Reference 16

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Source-reported events for the cited work

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Observation dca6ccbe-04e8-416b-a198-b3e43d84790c · outbound

This paper cites Nonparametric generative modeling with conditional sliced-wasserstein flows.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Nonparametric generative modeling with conditional sliced-wasserstein flows

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.594905Z

Source-reported events for the cited work

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Observation 9c05ee5c-25bb-4bc6-ab58-d18add052bae · outbound

This paper cites Variational wasserstein gradient flow.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Variational wasserstein gradient flow

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.437353Z

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Observation 229aa67d-d793-42aa-9b27-40f6001bf307 · outbound

This paper cites Measure transport with kernel stein discrepancy.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Measure transport with kernel stein discrepancy

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.364619Z

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Observation 037ee1aa-565d-4b6f-a22a-821558fba5e4 · outbound

This paper cites Learning generative models with sinkhorn divergences.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Learning generative models with sinkhorn divergences

Reference 20

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Source-reported events for the cited work

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Observation 8b965bca-9619-408a-8651-220803390032 · outbound

This paper cites Generative adversarial networks.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Generative adversarial networks

Reference 21

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Source-reported events for the cited work

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Observation 50ce28d0-0d0b-43b1-911b-5b7231e185be · outbound

This paper cites Generative sliced MMD flows with R iesz kernels.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Generative sliced MMD flows with R iesz kernels

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.327460Z

Source-reported events for the cited work

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Observation a2acc561-9ab4-4ae6-932d-145c24027289 · outbound

This paper cites E., Martin, C.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis E., Martin, C

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.307796Z

Source-reported events for the cited work

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Observation 6de185af-e5cb-4728-9401-db62f41a84a7 · outbound

This paper cites Kernel stein discrepancy descent.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Kernel stein discrepancy descent

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.289443Z

Source-reported events for the cited work

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Observation ed4b874f-830e-494c-80b9-b19cade3980e · outbound

This paper cites Mmd gan: Towards deeper understanding of moment matching network.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Mmd gan: Towards deeper understanding of moment matching network

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.219356Z

Source-reported events for the cited work

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Observation a6c766d7-40b3-47a0-ab8e-5c6da4ba98df · outbound

This paper cites and Moosmueller, C.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis and Moosmueller, C

Reference 26

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Source-reported events for the cited work

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Observation e78aa22e-eb3c-4cfe-975d-a830ee8042e0 · outbound

This paper cites Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport and diffusions.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport and diffusions

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.081724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 06ec429e-7b3c-4e0c-ba2a-a98086643c58 · outbound

This paper cites Fast optimal transport through sliced generalized wasserstein geodesics.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Fast optimal transport through sliced generalized wasserstein geodesics

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:25.007161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f4d1f52-10e9-4699-a6bb-ba864ee07683 · outbound

This paper cites Minimax confidence intervals for the sliced wasserstein distance.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Minimax confidence intervals for the sliced wasserstein distance

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.987098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5535fc5d-0444-477d-9701-3c87053b7d6f · outbound

This paper cites A Mean Field View of the Landscape of Two-Layer Neural Networks.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis A Mean Field View of the Landscape of Two-Layer Neural Networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.969929Z

Source-reported events for the cited work

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Observation 2cb2b8df-d374-4331-8d1b-8514948b350e · outbound

This paper cites Non-asymptotic convergence bounds for wasserstein approximation using point clouds.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Non-asymptotic convergence bounds for wasserstein approximation using point clouds

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.924387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 70f1989b-d652-4c14-a5b9-d48cd9d7744a · outbound

This paper cites Statistical and topological properties of sliced probability divergences.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Statistical and topological properties of sliced probability divergences

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.805463Z

Source-reported events for the cited work

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Observation c8c40170-9854-4116-bb43-b43b019843e9 · outbound

This paper cites and Ho, N.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis and Ho, N

Reference 33

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Source-reported events for the cited work

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Observation d63ba732-8bed-4052-83a7-47b26083d8b4 · outbound

This paper cites Statistical, robustness, and computational guarantees for sliced wasserstein distances.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Statistical, robustness, and computational guarantees for sliced wasserstein distances

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.564310Z

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Observation 1e2bd207-219c-4f45-bc72-7c89156d75eb · outbound

This paper cites First-order methods almost always avoid saddle points: The case of vanishing step-sizes.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis First-order methods almost always avoid saddle points: The case of vanishing step-sizes

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.548769Z

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Observation e31fdb85-7d67-4348-8fe1-8d438d357867 · outbound

This paper cites Computational optimal transport: With applications to data science.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Computational optimal transport: With applications to data science

Reference 36

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Source-reported events for the cited work

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Observation 5b39b9c6-ffcc-4c50-bd03-a7c098de85e4 · outbound

This paper cites On the sequential convergence of Lloyd's algorithms.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis On the sequential convergence of Lloyd's algorithms

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.520347Z

Source-reported events for the cited work

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Observation bfc59f07-d457-4180-a2fb-3adc0a961208 · outbound

This paper cites Wasserstein barycenter and its application to texture mixing.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Wasserstein barycenter and its application to texture mixing

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T15:18:23.234555Z

Source-reported events for the cited work

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Observation 5a32b71c-fa47-46b5-80dd-528de02d581e · outbound

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Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Unresolved cited work

Reference 39

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Source-reported events for the cited work

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Observation 063dd261-b2c6-426b-9f21-a016bb251f8d · outbound

This paper cites Orthogonal estimation of wasserstein distances.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Orthogonal estimation of wasserstein distances

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.461478Z

Source-reported events for the cited work

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Observation 09ac7972-cc06-458a-8665-fcb674f8c083 · outbound

This paper cites The Wasserstein Proximal Gradient Algorithm.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis The Wasserstein Proximal Gradient Algorithm

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.428109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8c2c1b61-ba02-4f8c-85e4-61df6845a86a · outbound

This paper cites Optimal transport for applied mathematicians.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Optimal transport for applied mathematicians

Reference 42

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Source-reported events for the cited work

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Observation b9853849-07f1-415c-8cfd-4b59d73e3991 · outbound

This paper cites Lagrangian discretization of variational problems in Wasserstein spaces.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Lagrangian discretization of variational problems in Wasserstein spaces

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.334561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a144de3-0c1b-452b-bb93-64584ce574c0 · outbound

This paper cites Properties of discrete sliced W asserstein losses.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Properties of discrete sliced W asserstein losses

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.154500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89e324b4-151f-42ff-9fb7-1e1c00f2d504 · outbound

This paper cites Reconstructing discrete measures from projections.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Reconstructing discrete measures from projections

Reference 45

Resolution: verified exact; doi, observed 2026-08-08T15:18:23.393426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 39afeaa0-f329-4942-9c37-46ea4812639f · outbound

This paper cites Optimal transport -- Old and new, volume 338.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Optimal transport -- Old and new, volume 338

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.047670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e9c73e6e-d052-424a-92b7-798bee5b5048 · outbound

This paper cites Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.028755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ce650dbb-701f-4868-9c1d-820b0429c78d · outbound

This paper cites and Liu, S.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis and Liu, S

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:24.009426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 63f278c5-fd22-4ab6-9743-42457f4e2a44 · outbound

This paper cites Monoflow: Rethinking divergence gans via the perspective of wasserstein gradient flows.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Monoflow: Rethinking divergence gans via the perspective of wasserstein gradient flows

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:18:23.991746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation e095bdf6-6fbd-4125-a7e7-6e910f726158 · inbound

Convergence Rates for Distribution Matching with Sliced Optimal Transport cites this paper.

Convergence Rates for Distribution Matching with Sliced Optimal Transport Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T01:09:06.138004Z

Source-reported events for the cited work

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Observation fe6d9b35-ee4a-428e-9fad-2f3217e34015 · inbound

Convergence of empirical subgradients for optimal transport-based objectives cites this paper.

Convergence of empirical subgradients for optimal transport-based objectives Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-06-29T11:23:21.271718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c027fcb4-05c4-4b1e-b218-0c44f56ad649 · inbound

Convergence of empirical subgradients for optimal transport-based objectives cites this paper.

Convergence of empirical subgradients for optimal transport-based objectives Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-14T18:41:00.296741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.