Pith. sign in

Paper Citation Record · LEDGER

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration

As of 21 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2501.15964.

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

pith.paper-citation-record.v1
2501.15964 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:51:31.358081Z

measured 32 of 32 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

32 of 32 outbound references displayed

  • verified exact4
  • verified fuzzy21
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a63672e4-cb9e-48c3-83bc-289b8449364a · outbound

This paper cites API design for machine learning software: experiences from the scikit-learn project.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration API design for machine learning software: experiences from the scikit-learn project

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.275303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.275303Z digest=sha256:c44d14535fce27f91022cf21c77a91298845244f09766d932168f62f55cdb7ac

Observation 005a4fbe-5e89-4545-94c9-0544db31940a · outbound

This paper cites HPR-LP: An implementation of an HPR method for solving linear programming.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration HPR-LP: An implementation of an HPR method for solving linear programming

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.279584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.279584Z digest=sha256:935e4c7efff50f87ae7d581c9663831840083e39c4dfa034108f6f6138acf056

Observation b3701ae4-cf2a-4e27-97dc-0ca03c081efd · outbound

This paper cites Splitting methods for convex clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Splitting methods for convex clustering

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.678309Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.282438Z digest=sha256:250654e5a4b957f5be9cd9d0cde671331f42bf03344c961cbe584a65ec95b214

Observation 64f06d3c-3834-4da9-b8b5-985914a89898 · outbound

This paper cites Recovering trees with convex clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Recovering trees with convex clustering

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.670164Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.285244Z digest=sha256:e220d021cf2c5013f5c9d55c1278bfee8984c6ddc17e59f2053d398e8bddb44e

Observation 6c922804-bc9c-4f9a-bfc1-c9bc01bd1bc1 · outbound

This paper cites Provable convex co-clustering of tensors.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Provable convex co-clustering of tensors

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.663244Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.288338Z digest=sha256:bfaae495d4c78a8d6706421b514a51907d6d45e6c88fb2d6f27bda245ca2eb46

Observation 5ca98147-db52-4307-86d6-9f4da3478707 · outbound

This paper cites Fast tree inference with weighted fusion penalties.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Fast tree inference with weighted fusion penalties

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.656174Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.291051Z digest=sha256:9fd38f6f22a737005e8d785be08dfc7cf0b13be21e6b43e6302204040b1a0550

Observation e038a585-aac0-4650-a09b-68a4e18db74a · outbound

This paper cites Libras Movement.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Libras Movement

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.647932Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.293773Z digest=sha256:0ea6fb869ad3514e3771b762f687803432b2968ac32f036589e357bb3e036a37

Observation d4ded494-2d26-4e3a-a2e7-9cb3dab45c09 · outbound

This paper cites Convex hierarchical clustering for graph-structured data.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Convex hierarchical clustering for graph-structured data

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.640656Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.296261Z digest=sha256:06038ba0523b01dc1028b42854d69bbd30fb07b554832e7f2e6b6dffff2ea355

Observation 404da45e-7b3f-4053-a21d-6713cdb0cf39 · outbound

This paper cites Sum-of-norms clustering does not separate nearby balls.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Sum-of-norms clustering does not separate nearby balls

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-10T13:51:31.486990Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.299129Z digest=sha256:1bf34fd7f4a48eb03980d9692151c4b51fc12d9124e0703cc42253259abc16f1

Observation bb74aa90-b5ce-4059-b00f-eb6243b5f89b · outbound

This paper cites A review of convex clustering from multiple perspectives: models, optimizations, statistical properties, applications, and connections.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration A review of convex clustering from multiple perspectives: models, optimizations, statistical properties, applications, and connections

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.633166Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.301907Z digest=sha256:6f061b82222fce51229d81681f58fc42e6327f445eaf43143e964c819e430746

Observation 8e5f6c4b-1e01-4e63-9af5-495dcd35f6b0 · outbound

This paper cites Clusterpath an algorithm for clustering using convex fusion penalties.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Clusterpath an algorithm for clustering using convex fusion penalties

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.625003Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.304879Z digest=sha256:c70040ce0908834a247208d49d766d25ecdd0b488c42211dfbc3fac0ffcfadcf

Observation eed104c3-4831-4b8b-a570-7e738d7ee35e · outbound

This paper cites Recovery of a mixture of G aussians by sum-of-norms clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Recovery of a mixture of G aussians by sum-of-norms clustering

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.617389Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.307548Z digest=sha256:a58b3a38394a292083f44ca3e8a59b623b0ff77670aedf805a7e761f7b3ce843

Observation 75ea5753-808b-4d0f-9fe6-29be0310300d · outbound

This paper cites Gradient-based learning applied to document recognition.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Gradient-based learning applied to document recognition

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.309948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.309948Z digest=sha256:ef00443b7bbdd981ae37cb8a93a1d27df4112a7349f7e428821ebff084bad14a

Observation f7eddf9f-3b76-4c92-8ceb-6f5d4637df3e · outbound

This paper cites Biclustering via sparse singular value decomposition.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Biclustering via sparse singular value decomposition

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.604497Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.312360Z digest=sha256:8d1cfa3b1dbbe93ffafd5a51d443621ba51139220221f297a5e75afa5ea4741e

Observation e1586319-029e-4203-b499-7cf2b579d250 · outbound

This paper cites Clustering using sum-of-norms regularization: With application to particle filter output computation.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Clustering using sum-of-norms regularization: With application to particle filter output computation

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.597412Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.315108Z digest=sha256:1cf0f2804037c2611bad08aa15833ec0428c6d89d87176420bccc4c46b437260

Observation 32200592-9d08-4c66-b269-584365807f03 · outbound

This paper cites Columbia object image library (coil-20).

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Columbia object image library (coil-20)

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.588948Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.317902Z digest=sha256:dc870867ad9f0435cd4364d09428cc49267af06fd60222aa43bca42860313f5f

Observation fe6b0715-dab9-4ef7-8b99-27c4f00847ba · outbound

This paper cites Large steps in inverse rendering of geometry.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Large steps in inverse rendering of geometry

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.320158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.320158Z digest=sha256:4b8c2830985a6bb2e5b95669f3725ceaebd927befe1c47f4e171fa9bccf8266b

Observation 92f8ea89-cec9-4159-809b-7aa19e6d75f1 · outbound

This paper cites Numerical Optimization.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Numerical Optimization

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.580164Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.322460Z digest=sha256:adc88d79130ed3a12f3cda7bd709db53f1b82d125056ad60362a74713316d7bf

Observation 2784f65d-44ef-4f6c-870a-6052fa333387 · outbound

This paper cites Clustering by sum of norms: Stochastic incremental algorithm, convergence and cluster recovery.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Clustering by sum of norms: Stochastic incremental algorithm, convergence and cluster recovery

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.573130Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.324741Z digest=sha256:57c066084daf09b29c1dc1a7f75641f2c2e1c59cc7b31dc8bdb3c3f3cb4a4d9e

Observation d60b992c-3df9-4944-a075-0d52b80accf0 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Pytorch: An imperative style, high-performance deep learning library

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.327965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.327965Z digest=sha256:da6e2cf9fcc244018e9d1f174cb0b5405094e849c928896ce04593f3103245d8

Observation b5f1eb6f-06f4-4824-87a6-576c4d0f8b16 · outbound

This paper cites Convex clustering shrinkage.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Convex clustering shrinkage

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.561503Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.331104Z digest=sha256:bef71cef8c00c765a15e1da4c55ece2e4945b35be47ebbb48b5c90cf1843e346

Observation 800e87c1-3b03-4c5c-81d8-f4b6d84cb006 · outbound

This paper cites Convex clustering via l_1 fusion penalization.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Convex clustering via l_1 fusion penalization

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.555039Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.334001Z digest=sha256:3d919e7706244680fc9a5ef433eb77dd8f7daf8c733461ff4cae0c5d893cbe50

Observation b781bbe9-288c-4f4c-bda4-cf145bcacee2 · outbound

This paper cites Convex clustering: Model, theoretical guarantee and efficient algorithm.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Convex clustering: Model, theoretical guarantee and efficient algorithm

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.336382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.336382Z digest=sha256:8b11dee9910d83d10e761d758b189be77ed185f9fc13830c692bce8bc3658bee

Observation 6fc9e18c-fa09-478a-8810-1a479f872743 · outbound

This paper cites Accelerating preconditioned ADMM via degenerate proximal point mappings.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Accelerating preconditioned ADMM via degenerate proximal point mappings

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-10T13:51:31.414226Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.338681Z digest=sha256:6bdbbd4e6daab410be43d0929ab417f1e6ffa3ce8f2e03dc33725b6ae7ca6577

Observation 9575dbd2-6492-4fc5-a10c-5c284e628af0 · outbound

This paper cites Statistical properties of convex clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Statistical properties of convex clustering

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.543721Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.340994Z digest=sha256:965ab138a5c8371b5073d6bfa168df2c8e2a42d685f4732d8d48ca0d98fe83e4

Observation a0614c00-223b-4e50-8f81-d3dbe41d2f31 · outbound

This paper cites Sparse convex clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Sparse convex clustering

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.536946Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.342860Z digest=sha256:faef8ed1cf0c3f2c31e9465b1cb1b6723681a81f98d26b26023b95debf72ae2e

Observation 5902eb9a-1e77-4b92-a538-dc5c954ec7c4 · outbound

This paper cites Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-10T13:51:31.404114Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.344951Z digest=sha256:fcbfff0cefed312c9fcb41fbd2f83d2bccedb3dde3f5cc338153625300b6e0f4

Observation f4bd3e5a-563a-4587-8fdf-a41acbd32548 · outbound

This paper cites An efficient semismooth N ewton based algorithm for convex clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration An efficient semismooth N ewton based algorithm for convex clustering

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.529351Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.347628Z digest=sha256:00c76ba3d183e8ae91a3401f711ef6bb3401394084aee0c13701db2b5f523077

Observation b45215aa-9747-4321-9700-c3bff09584c5 · outbound

This paper cites A dimension reduction technique for large-scale structured sparse optimization problems with application to convex clustering.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration A dimension reduction technique for large-scale structured sparse optimization problems with application to convex clustering

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.518718Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.349667Z digest=sha256:f0ab83154bca8294fd0e470d64ff91caa425ddd617d066bdbfefe0256960c414

Observation 8a2e57ff-68b1-45e4-8e6f-369d1e365b3b · outbound

This paper cites An Efficient HPR Algorithm for the Wasserstein Barycenter Problem with $O({Dim(P)}/\varepsilon)$ Computational Complexity.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration An Efficient HPR Algorithm for the Wasserstein Barycenter Problem with $O({Dim(P)}/\varepsilon)$ Computational Complexity

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T13:51:31.352042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:51:31.352042Z digest=sha256:43b9e2ae222f1cd7437adf3b9eb6c98de73ad9f68e8dcc00f212db284ccd82f9

Observation de0e598c-0ecd-41a3-bb8b-9e1e18c63eac · outbound

This paper cites HOT: An Efficient Halpern Accelerating Algorithm for Optimal Transport Problems.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration HOT: An Efficient Halpern Accelerating Algorithm for Optimal Transport Problems

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-10T13:51:31.385293Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.355331Z digest=sha256:59c4c1652ddf79a1e072cda9cefeab006a525dde996faadd04e2bd5c1433bb13

Observation 0419f92f-ff89-4a1c-91be-1f6b08b93958 · outbound

This paper cites Convex optimization procedure for clustering: Theoretical revisit.

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration Convex optimization procedure for clustering: Theoretical revisit

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T13:51:31.508670Z

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.

source=arxiv_source observed=2026-08-10T13:51:31.358081Z digest=sha256:de1a016835edb14fbfbe72ed13bb1a4965a5629cb7ca3079db3992b7ec59299c

Pith citing papers

No inbound Pith citation observations are available.