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Paper Citation Record · LEDGER

Adversarial Transform Particle Filters

As of 11 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2502.06165.

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

pith.paper-citation-record.v1
2502.06165 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:36:50.900513Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

62 of 62 outbound references displayed

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  • verified fuzzy48
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a2effe28-7f85-414c-8990-e13703b2c11d · outbound

This paper cites Importance sampling: Intrinsic dimension and computational cost.

Adversarial Transform Particle Filters Importance sampling: Intrinsic dimension and computational cost

Reference 1

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Observation 2dff8d60-960a-4a7f-b153-a44d37d7a338 · outbound

This paper cites Empirical processes associated with v-statistics and a class of estimators under random censoring.

Adversarial Transform Particle Filters Empirical processes associated with v-statistics and a class of estimators under random censoring

Reference 2

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Observation a24924a0-4933-44d9-bbf9-292e245d4632 · outbound

This paper cites Kernels for vector-valued functions: A review.

Adversarial Transform Particle Filters Kernels for vector-valued functions: A review

Reference 3

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Observation 75d4d474-43f2-4185-aff1-9421ea1926b6 · outbound

This paper cites An ensemble adjustment kalman filter for data assimilation.

Adversarial Transform Particle Filters An ensemble adjustment kalman filter for data assimilation

Reference 4

Resolution
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Observation 27a1b008-8b5b-41d8-a600-946ed4ad4c13 · outbound

This paper cites An adaptive covariance inflation error correction algorithm for ensemble filters.

Adversarial Transform Particle Filters An adaptive covariance inflation error correction algorithm for ensemble filters

Reference 5

Resolution
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Observation 877d7fb3-0d92-495f-996f-c65cec82a16f · outbound

This paper cites A non-gaussian ensemble filter update for data assimilation.

Adversarial Transform Particle Filters A non-gaussian ensemble filter update for data assimilation

Reference 6

Resolution
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Observation 3a99cfa2-aed2-4698-aca3-33db9d4ac79c · outbound

This paper cites Wasserstein generative adversarial networks.

Adversarial Transform Particle Filters Wasserstein generative adversarial networks

Reference 7

Resolution
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Source-reported events for the cited work

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Observation e61f3039-a0bd-4179-bf6b-1e8fe05b16f4 · outbound

This paper cites A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking.

Adversarial Transform Particle Filters A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking

Reference 8

Resolution
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Source-reported events for the cited work

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Observation fabd71fe-a04c-4e1b-9632-55e64b3ccaeb · outbound

This paper cites Sequential data assimilation techniques in oceanography.

Adversarial Transform Particle Filters Sequential data assimilation techniques in oceanography

Reference 9

Resolution
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Observation 1f628c66-a6ab-4136-83b0-894a51b1fb02 · outbound

This paper cites Adaptive sampling with the ensemble transform kalman filter.

Adversarial Transform Particle Filters Adaptive sampling with the ensemble transform kalman filter

Reference 10

Resolution
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Observation 54f95027-cf31-4210-afe9-710c58808275 · outbound

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Adversarial Transform Particle Filters Unresolved cited work

Reference 11

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Observation aca19297-26de-4137-9c1b-d542186ea7a6 · outbound

This paper cites On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension.

Adversarial Transform Particle Filters On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension

Reference 12

Resolution
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Observation a225e30c-228a-4bee-8fc2-e5bcf031e283 · outbound

This paper cites Sequential data assimilation with a nonlinear quasi-geostrophic model using monte carlo methods to forecast error statistics.

Adversarial Transform Particle Filters Sequential data assimilation with a nonlinear quasi-geostrophic model using monte carlo methods to forecast error statistics

Reference 13

Resolution
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This paper cites The ensemble kalman filter: Theoretical formulation and practical implementation.

Adversarial Transform Particle Filters The ensemble kalman filter: Theoretical formulation and practical implementation

Reference 14

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Source-reported events for the cited work

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Observation 6d782784-2554-4db8-9ea9-97515a455382 · outbound

This paper cites Variational Wasserstein gradient flow.

Adversarial Transform Particle Filters Variational Wasserstein gradient flow

Reference 15

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Observation 7612a85a-450c-4c20-8f85-c21037bb52c9 · outbound

This paper cites Data assimilation for the geosciences: From theory to application.

Adversarial Transform Particle Filters Data assimilation for the geosciences: From theory to application

Reference 16

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Observation ad2e29cc-d1f8-46bc-841e-5bebb85ee5db · outbound

This paper cites Covariance tapering for interpolation of large spatial datasets.

Adversarial Transform Particle Filters Covariance tapering for interpolation of large spatial datasets

Reference 17

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Observation 7897f824-597f-4ef1-8516-f2244f88983a · outbound

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Adversarial Transform Particle Filters Gamerman

Reference 18

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Adversarial Transform Particle Filters Unresolved cited work

Reference 19

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Observation fea7cb6e-81fa-423a-8656-83455c19adda · outbound

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Adversarial Transform Particle Filters Generative adversarial nets

Reference 20

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Observation 2f49ec7b-b975-4435-915f-cc2dfeb9fa1a · outbound

This paper cites Novel approach to nonlinear/non-gaussian bayesian state estimation.

Adversarial Transform Particle Filters Novel approach to nonlinear/non-gaussian bayesian state estimation

Reference 21

Resolution
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Source-reported events for the cited work

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Adversarial Transform Particle Filters A Distribution-Free Theory of Nonparametric Regression

Reference 22

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Source-reported events for the cited work

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Adversarial Transform Particle Filters Advances in importance sampling

Reference 23

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Adversarial Transform Particle Filters Efficient data assimilation for spatiotemporal chaos: A local ensemble transform kalman filter

Reference 24

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Adversarial Transform Particle Filters The variational formulation of the fokker--planck equation

Reference 25

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Adversarial Transform Particle Filters Unresolved cited work

Reference 26

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Adversarial Transform Particle Filters Understanding the ensemble kalman filter

Reference 27

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Source-reported events for the cited work

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Adversarial Transform Particle Filters Ensemble kalman methods for high-dimensional hierarchical dynamic space-time models

Reference 28

Resolution
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Adversarial Transform Particle Filters Introduction to kalman filter and its applications

Reference 29

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Adversarial Transform Particle Filters A note on importance sampling using standardized weights

Reference 30

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Adversarial Transform Particle Filters Recursive monte carlo filters: algorithms and theoretical analysis

Reference 31

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Adversarial Transform Particle Filters Bellman filtering and smoothing for state--space models

Reference 32

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Source-reported events for the cited work

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Adversarial Transform Particle Filters A moment matching ensemble filter for nonlinear non-gaussian data assimilation

Reference 33

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Adversarial Transform Particle Filters How well generative adversarial networks learn distributions

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Adversarial Transform Particle Filters Stein variational gradient descent: A general purpose bayesian inference algorithm

Reference 35

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Adversarial Transform Particle Filters Implicit regularization in nonconvex statistical estimation: Gradient descent converges linearly for phase retrieval and matrix completion

Reference 36

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 2a6ca180-78c6-4952-97ef-10a448b42fef · outbound

This paper cites Concentration inequalities for log-concave distributions with applications to random surface fluctuations.

Adversarial Transform Particle Filters Concentration inequalities for log-concave distributions with applications to random surface fluctuations

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.350284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.783908Z digest=sha256:c8e69c63ce4ecf3fcf9e445a46f88b13a3d0127fa1270e63e1cca0a83b3053af

Observation d0a95539-d485-43aa-9d61-6ac61d78d5f3 · outbound

This paper cites Fastslam 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges.

Adversarial Transform Particle Filters Fastslam 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.335422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.788165Z digest=sha256:3762586c44430eea688fb8350c935bd7361d9613d6f0639d76297fb1546b7a5f

Observation f35d1f33-a150-4257-814f-d856b6ebc675 · outbound

This paper cites Rao-blackwellised particle filtering for dynamic bayesian networks.

Adversarial Transform Particle Filters Rao-blackwellised particle filtering for dynamic bayesian networks

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.320475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.792563Z digest=sha256:38c56644f69f86574583543486c6734106476922941d8724fb9635ce695fdf44

Observation 57db7af2-2e73-4398-9f87-6931e2be0c13 · outbound

This paper cites Improving regularised particle filters.

Adversarial Transform Particle Filters Improving regularised particle filters

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.305621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.796739Z digest=sha256:572150e9cf6fd00c22317a8c36f17965fd2f69c8f798903ce1bd5e1f65d1a901

Observation a479a142-8da8-4934-ba1c-571006e03854 · outbound

This paper cites Merging particle filter for sequential data assimilation.

Adversarial Transform Particle Filters Merging particle filter for sequential data assimilation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.290995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.801115Z digest=sha256:b103798663babd789fcfccba7e57c9e758f43b35b8f887b2c8bf5ad639801f66

Observation c9e41938-5a75-4797-b482-bcae75e0d81f · outbound

This paper cites Diffusion models are minimax optimal distribution estimators.

Adversarial Transform Particle Filters Diffusion models are minimax optimal distribution estimators

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.276503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.805538Z digest=sha256:200ba86e9bc50bf3101de63c98f22ee46c8c6a417830fa54e2698476935c6cd3

Observation fb703fcf-5f04-4b79-9631-88992f8278ee · outbound

This paper cites Optimal approximation of piecewise smooth functions using deep relu neural networks.

Adversarial Transform Particle Filters Optimal approximation of piecewise smooth functions using deep relu neural networks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.261455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.809869Z digest=sha256:9c9186c4b4899802cc28a81749b474b2989e989138442ae25d717501cd043e86

Observation 2d842c8e-80e9-4747-8288-3098a8b7b0a7 · outbound

This paper cites A localized particle filter for high-dimensional nonlinear systems.

Adversarial Transform Particle Filters A localized particle filter for high-dimensional nonlinear systems

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.245182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.814431Z digest=sha256:00b6a68fb36266514d6ca1c4344c6d9be51daad09228e09bed330ff86603367c

Observation f29d1767-32f9-4db8-83c2-1e6352b4d405 · outbound

This paper cites Overview of global data assimilation developments in numerical weather-prediction centres.

Adversarial Transform Particle Filters Overview of global data assimilation developments in numerical weather-prediction centres

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.230256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.818589Z digest=sha256:f7df82f8ec7ffdfbab6d050577184903759bcfe94d264cd429caff1b3e104bf7

Observation a5339959-67a4-4c2a-bab1-2f93c16b5fc8 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Adversarial Transform Particle Filters Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T16:36:50.823081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:50.823081Z digest=sha256:0dbb49781128583c258812b6c05b435713998bdfedc379cca3bc343efc943ca4

Observation 4d22b2b2-0d18-412b-88df-45664f1db368 · outbound

This paper cites A nonparametric ensemble transform method for bayesian inference.

Adversarial Transform Particle Filters A nonparametric ensemble transform method for bayesian inference

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.214851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.828038Z digest=sha256:233b621fed57f849b801a21bb81c49e48df05e8e7d1882367df863713b780729

Observation b4c7bded-fa3d-4afd-9163-31918015726a · outbound

This paper cites Venezuelan rainfall data analysed by using a bayesian space--time model.

Adversarial Transform Particle Filters Venezuelan rainfall data analysed by using a bayesian space--time model

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.198567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.832663Z digest=sha256:a59713b7b67fe3ea0b4a12c0259f436d2e180de1a976b6513aac1c3719228feb

Observation 67b8f2f7-bc02-4118-86a8-161d5fc1a3b7 · outbound

This paper cites Log-concavity and strong log-concavity: a review.

Adversarial Transform Particle Filters Log-concavity and strong log-concavity: a review

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.183235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.837241Z digest=sha256:2733a010465cac60a721a7c92230db9a8e7e92c5a529215257bdb3da5e5b8430

Observation d99d71ee-da7f-4d94-9a4c-f8c455d1f8d3 · outbound

This paper cites Approximation theorems of mathematical statistics.

Adversarial Transform Particle Filters Approximation theorems of mathematical statistics

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T16:36:50.842095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:50.842095Z digest=sha256:c154fd2b87cadfe32ac8e193a09d71cf0955956f0ac6a3c6a38380ee42d786e2

Observation 201cc44c-0827-4b0a-8672-569cdbbc609b · outbound

This paper cites Shephard and M.

Adversarial Transform Particle Filters Shephard and M

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.158005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.846869Z digest=sha256:b763e0756ba8a5e5eb90c3b4ddbde67d88afcba35fd2a94e957ab379b32f978d

Observation 72637cc5-0528-4004-b3b8-a0e5c7e5c2cc · outbound

This paper cites Maximum mean discrepancy.

Adversarial Transform Particle Filters Maximum mean discrepancy

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.144096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.852025Z digest=sha256:59776417b3ed9c24d9336d5fc88044842baca175d833b3b02f275984bad4c3c9

Observation 2b77c6b8-1d20-40f3-bf01-8d995cb3da50 · outbound

This paper cites Obstacles to high-dimensional particle filtering.

Adversarial Transform Particle Filters Obstacles to high-dimensional particle filtering

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.129764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.856880Z digest=sha256:fd4524266dd36f4393294eab543699033e1be5ea7946de56b79460e9123877d8

Observation c999576f-eb05-47e7-8e24-6f1d23a09e1e · outbound

This paper cites High-dimensional ensemble kalman filter with localization, inflation, and iterative updates.

Adversarial Transform Particle Filters High-dimensional ensemble kalman filter with localization, inflation, and iterative updates

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.114186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.861592Z digest=sha256:2c3fcd64443c37be8bbaccbb1e736db31dc4fc1fa932287d9201c5e82339cbc2

Observation 15e5f6e0-56be-43e8-860e-51d66bff6288 · outbound

This paper cites Adaptivity of deep relu network for learning in besov and mixed smooth besov spaces: optimal rate and curse of dimensionality.

Adversarial Transform Particle Filters Adaptivity of deep relu network for learning in besov and mixed smooth besov spaces: optimal rate and curse of dimensionality

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.097185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.866273Z digest=sha256:41cd0ac8b32f5e9b9708c5adf4fcdd18c1423eefd0eb6c03ab41bf7405588012

Observation 93fede82-ad61-4204-9c2d-2f98a4164bbf · outbound

This paper cites High-Dimensional Statistics: A Non-Asymptotic Viewpoint.

Adversarial Transform Particle Filters High-Dimensional Statistics: A Non-Asymptotic Viewpoint

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T16:36:50.871233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:50.871233Z digest=sha256:10af05232de5433ccf4c47481ba3cb2801671ff07e9832db117a5454eb1c36e3

Observation cf4fe03d-b066-42fe-a29b-c6e67160b7f3 · outbound

This paper cites The implicit and explicit regularization effects of dropout.

Adversarial Transform Particle Filters The implicit and explicit regularization effects of dropout

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.081248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.876167Z digest=sha256:9a4029c548a6a8c81963ed8b78b98b3d106ca3834e07d44203343079617cfb12

Observation 80bc8440-eac8-4469-8dbe-b2cafaadaaa7 · outbound

This paper cites Bayesian learning via stochastic gradient langevin dynamics.

Adversarial Transform Particle Filters Bayesian learning via stochastic gradient langevin dynamics

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.065991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.880862Z digest=sha256:6740eb9bb1c4159131a27c042dea46cdef00fe9e7edaf259f234a02a754e4efa

Observation 0ffa4ff8-1a0e-4979-b84d-2686c6b4e598 · outbound

This paper cites A note on the particle filter with posterior gaussian resampling.

Adversarial Transform Particle Filters A note on the particle filter with posterior gaussian resampling

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.050561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.885629Z digest=sha256:1da8531d24f93d4d5f2a5e8fe10be350c2ad7d21fc8a76cd052a69fca7a46a20

Observation 6002fc41-b440-4c07-91a0-75e65f43cca4 · outbound

This paper cites Normalizing flow neural networks by jko scheme.

Adversarial Transform Particle Filters Normalizing flow neural networks by jko scheme

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:51.034366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T16:36:50.890622Z digest=sha256:8b639fe3fa83ccf4c7ea38e4adb2ed2808db85ed1fd0870799646e9362792577

Observation 74abe2e2-e515-4805-994b-41348eddbce1 · outbound

This paper cites On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces.

Adversarial Transform Particle Filters On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-08T16:36:50.895385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:50.895385Z digest=sha256:cd8783b3c82158210158358e857df421d5e03cadc950822db4d97eff25e18a5f

Observation 6201f0b9-e3e8-43c8-8f73-b1701b7ed45f · outbound

This paper cites write newline.

Adversarial Transform Particle Filters write newline

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-08T16:36:50.900513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:50.900513Z digest=sha256:15e34a6b977ea04ae36911b003ed371af6607c98cfcbf57e605b86479b183d96

Pith citing papers

No inbound Pith citation observations are available.