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Paper Citation Record · LEDGER

Initialization and training of matrix product state probabilistic models

As of 16 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2505.06419.

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

pith.paper-citation-record.v1
2505.06419 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:47:55.574556Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:47:04.538683Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T06:29:00.579434Z

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation 8ec4ff60-0cf4-40b3-809f-00658edcf611 · outbound

This paper cites Larochelle and I.

Initialization and training of matrix product state probabilistic models Larochelle and I

Reference 1

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Observation cd600696-b04a-4a4b-94da-b54508194d66 · outbound

This paper cites Germain, K.

Initialization and training of matrix product state probabilistic models Germain, K

Reference 2

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Observation 1b8643ae-1c21-4781-9a92-9eaf531ce16f · outbound

This paper cites PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications.

Initialization and training of matrix product state probabilistic models PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications

Reference 3

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Observation c389c749-5c2a-4118-9910-9c13121d8e1d · outbound

This paper cites Auto-Encoding Variational Bayes.

Initialization and training of matrix product state probabilistic models Auto-Encoding Variational Bayes

Reference 4

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Observation fb7842a4-b2ec-44fc-8e71-fdf6e8262de1 · outbound

This paper cites LeCun, S.

Initialization and training of matrix product state probabilistic models LeCun, S

Reference 5

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 4e2cf00b-33ff-4858-9a45-40455e4d044f · outbound

This paper cites Rezende and S.

Initialization and training of matrix product state probabilistic models Rezende and S

Reference 6

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Observation cd1256e8-71c6-40a4-a0bf-f8e4498d4aff · outbound

This paper cites Goodfellow, J.

Initialization and training of matrix product state probabilistic models Goodfellow, J

Reference 7

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Observation 1a1cd3c4-0369-4b1b-91f3-ee80ce21af18 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Initialization and training of matrix product state probabilistic models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 8

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Observation 949a5e4f-6abe-4d27-8fa3-4339ba296081 · outbound

This paper cites an unresolved cited work.

Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 9

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This paper cites Generative modeling via tensor train sketching.

Initialization and training of matrix product state probabilistic models Generative modeling via tensor train sketching

Reference 10

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Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 11

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Observation e24439df-5176-41ac-a7b5-cead8f978d91 · outbound

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Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 12

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Observation 22995831-5b13-4001-b875-495df66d7749 · outbound

This paper cites an unresolved cited work.

Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 13

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Observation b8c075a3-4667-45b7-8065-a48701609a9a · outbound

This paper cites Glasser, R.

Initialization and training of matrix product state probabilistic models Glasser, R

Reference 14

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9b707c3f-e1c7-482b-aa71-469afc5228cb · outbound

This paper cites Cramer, M.

Initialization and training of matrix product state probabilistic models Cramer, M

Reference 15

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Observation 9c9b1f37-8c51-49d1-b13d-71388055d429 · outbound

This paper cites Lanyon, C.

Initialization and training of matrix product state probabilistic models Lanyon, C

Reference 16

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Observation 80794ef4-a2f5-4423-a5a4-2901d898908a · outbound

This paper cites Mitarai, M.

Initialization and training of matrix product state probabilistic models Mitarai, M

Reference 17

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Observation 7781ffe2-5de4-41e4-a1df-a997cb121c01 · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

Initialization and training of matrix product state probabilistic models PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 18

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Observation 386e3de2-5141-4d96-8d45-cdfc10c91182 · outbound

This paper cites Schuld, V.

Initialization and training of matrix product state probabilistic models Schuld, V

Reference 19

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Observation c14b7c24-fa72-4752-ac81-162dff9cb04e · outbound

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Initialization and training of matrix product state probabilistic models Glorot and Y

Reference 20

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Observation 5ae8e4a8-7213-4c7c-b527-8c6768ad971e · outbound

This paper cites Pascanu, T.

Initialization and training of matrix product state probabilistic models Pascanu, T

Reference 21

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Observation e1dc2504-7259-4dad-acb2-edd5e84cb3d6 · outbound

This paper cites Erhan, A.

Initialization and training of matrix product state probabilistic models Erhan, A

Reference 22

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Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 23

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Observation cdcedbb4-11da-4835-a1bb-845087ac240f · outbound

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Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 24

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Observation 75dd96f4-855f-400b-a369-0b9780b36461 · outbound

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Initialization and training of matrix product state probabilistic models Cerezo, A

Reference 25

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Observation 67408481-6589-4ee6-8b60-d9da4ae36651 · outbound

This paper cites Cerezo and P.

Initialization and training of matrix product state probabilistic models Cerezo and P

Reference 26

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Observation 760fad6d-237a-43df-87f0-8af73eaac771 · outbound

This paper cites Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps.

Initialization and training of matrix product state probabilistic models Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps

Reference 27

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This paper cites an unresolved cited work.

Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 28

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Observation 18777d4f-337b-44d7-89f5-757ac914bbaf · outbound

This paper cites Dborin, F.

Initialization and training of matrix product state probabilistic models Dborin, F

Reference 29

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Initialization and training of matrix product state probabilistic models Vogel and H

Reference 30

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Observation faba8537-4c7b-4d7a-963f-69f75ac247a4 · outbound

This paper cites Leonhardt, Physical review letters74, 4101 (1995).

Initialization and training of matrix product state probabilistic models Leonhardt, Physical review letters74, 4101 (1995)

Reference 31

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Observation c2de9c4e-4419-41a3-a5ed-5cec7bec88f8 · outbound

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Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 32

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Observation a3426119-f8f1-4e47-bfb5-bdb4c6bac099 · outbound

This paper cites Torlai, G.

Initialization and training of matrix product state probabilistic models Torlai, G

Reference 33

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Observation 068c1df9-8690-4391-99b1-2759465d860f · outbound

This paper cites Haegeman, J.

Initialization and training of matrix product state probabilistic models Haegeman, J

Reference 34

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Observation fef413be-93d7-4417-872f-6a1be42c25e9 · outbound

This paper cites Haegeman, C.

Initialization and training of matrix product state probabilistic models Haegeman, C

Reference 35

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Observation ba8fd5f1-e313-4eb6-a156-8e2e1c6d1c08 · outbound

This paper cites Oseledets and E.

Initialization and training of matrix product state probabilistic models Oseledets and E

Reference 36

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Observation 872af625-e2b1-4c46-af42-ba07549e78e8 · outbound

This paper cites an unresolved cited work.

Initialization and training of matrix product state probabilistic models Unresolved cited work

Reference 37

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Observation a05bdd94-98c6-4416-88bb-35a6e9f32d0d · outbound

This paper cites One likely explanation for the 2-site DMRG method encountering 12 local minima issues is that the truncation step in the 2-site DMRG is not variational.

Initialization and training of matrix product state probabilistic models One likely explanation for the 2-site DMRG method encountering 12 local minima issues is that the truncation step in the 2-site DMRG is not variational

Reference 38

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Pith citing papers

Observation f1beaea4-2809-479d-a96b-ee390cda11e6 · inbound

Efficient Finite Initialization with Partial Norms for Tensorized Neural Networks and Tensor Networks Algorithms cites this paper.

Efficient Finite Initialization with Partial Norms for Tensorized Neural Networks and Tensor Networks Algorithms Initialization and training of matrix product state probabilistic models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:29:00.583006Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-24T06:28:33.255228Z digest=sha256:82333f1abfca69ef50e11d318fdc65ee4db19ec7ec9b03edc375abc6ab504aeb

Observation ac3011a9-a28e-4013-918c-60e6e672f7f0 · inbound

Variational inference and density estimation with non-negative tensor train cites this paper.

Variational inference and density estimation with non-negative tensor train Initialization and training of matrix product state probabilistic models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T12:47:04.538683Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:47:04.538683Z digest=sha256:2c623cbe035e993045613f0a9c4ee4899ed863956e84f6d6942e0827fdbdc1dc