Paper Citation Record · LEDGER

Latent Matters: Learning Deep State-Space Models

As of 24 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2602.23050.

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

pith.paper-citation-record.v1
2602.23050 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:40:20.697672Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

29 of 29 outbound references displayed

verified exact0
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 61731aae-d428-47c3-aba5-5b8dcc2a407a · outbound

This paper cites Saurous, and Kevin Murphy.

Latent Matters: Learning Deep State-Space Models Saurous, and Kevin Murphy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:17.824066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b48feb9-49e3-4918-a547-5e3a5964e104 · outbound

This paper cites Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models.

Latent Matters: Learning Deep State-Space Models Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:17.887710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7426fcc2-ebbc-4b59-898f-086ff724ba97 · outbound

This paper cites Learning to Fly via Deep Model-Based Reinforcement Learning.arXiv preprint arXiv:: 2003.0887, 2020.

Latent Matters: Learning Deep State-Space Models Learning to Fly via Deep Model-Based Reinforcement Learning.arXiv preprint arXiv:: 2003.0887, 2020

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.000167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d9cd41d-aefa-4998-8d66-379568f8e349 · outbound

This paper cites Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio.

Latent Matters: Learning Deep State-Space Models Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.129347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d3e11f8-d615-4d74-9e82-1fe2b9c1b313 · outbound

This paper cites A recurrent latent variable model for sequential data.

Latent Matters: Learning Deep State-Space Models A recurrent latent variable model for sequential data

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.230618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ef93fbc-67b1-4b76-aa4b-51070f1fbc20 · outbound

This paper cites Probabilistic Recurrent State-Space Models.

Latent Matters: Learning Deep State-Space Models Probabilistic Recurrent State-Space Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.338510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02e0783a-9a38-4d3b-a154-e0ee54a2c8a0 · outbound

This paper cites Sequential Neural Models with Stochastic Layers.

Latent Matters: Learning Deep State-Space Models Sequential Neural Models with Stochastic Layers

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.433006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03c6f10c-d625-43f3-82c4-a7a429412eea · outbound

This paper cites A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning.

Latent Matters: Learning Deep State-Space Models A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.543690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d5b4b1e-0e35-4cef-99ac-4bb94c3a9032 · outbound

This paper cites Learning Latent Dynamics for Planning from Pixels.

Latent Matters: Learning Deep State-Space Models Learning Latent Dynamics for Planning from Pixels

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.606025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e306e184-06ea-452e-bbd9-461b921a94be · outbound

This paper cites beta-V AE: Learning Basic Visual Concepts with a Constrained Variational Framework.

Latent Matters: Learning Deep State-Space Models beta-V AE: Learning Basic Visual Concepts with a Constrained Variational Framework

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.666299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caf45551-007b-4624-a3fd-280f9cb72306 · outbound

This paper cites Jazwinski.Stochastic Processes and Filtering Theory.

Latent Matters: Learning Deep State-Space Models Jazwinski.Stochastic Processes and Filtering Theory

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.722827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67f09c1d-ba99-4b46-bce3-7feedebe1668 · outbound

This paper cites an unresolved cited work.

Latent Matters: Learning Deep State-Space Models Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.783598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 314845cb-ce9a-4727-bb78-ebb9ee328f87 · outbound

This paper cites Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data.

Latent Matters: Learning Deep State-Space Models Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.862286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3d057c2-a2d0-472f-a2d2-3300f87cade4 · outbound

This paper cites Unsupervised Real-Time Control through Variational Empowerment.

Latent Matters: Learning Deep State-Space Models Unsupervised Real-Time Control through Variational Empowerment

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:18.968473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcb5c753-d14c-4e24-b5af-5ea60fa917a2 · outbound

This paper cites Kingma and Max Welling.

Latent Matters: Learning Deep State-Space Models Kingma and Max Welling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.105050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f39720a-3611-46cb-9056-9245f686ecdc · outbound

This paper cites Learn- ing Hierarchical Priors in V AEs.

Latent Matters: Learning Deep State-Space Models Learn- ing Hierarchical Priors in V AEs

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.226797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20023ec9-329d-4171-a3ae-7cef1458819b · outbound

This paper cites Deep Kalman Filters.

Latent Matters: Learning Deep State-Space Models Deep Kalman Filters

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.344248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73c5b726-043d-4118-98b2-3ef879890d15 · outbound

This paper cites Deep Rao-Blackwellised Particle Filters for Time Series Forecasting.

Latent Matters: Learning Deep State-Space Models Deep Rao-Blackwellised Particle Filters for Time Series Forecasting

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.531559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f23fc6c9-655a-4553-8fb0-1795290c7ea6 · outbound

This paper cites Guided Policy Search.

Latent Matters: Learning Deep State-Space Models Guided Policy Search

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.632231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a210b646-9712-44dd-b973-468d40451cc4 · outbound

This paper cites Neal and Geoffrey E.

Latent Matters: Learning Deep State-Space Models Neal and Geoffrey E

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.710158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48ed9fea-b295-4ea9-abc8-504be456d3af · outbound

This paper cites Deep State Space Models for Time Series Forecasting.

Latent Matters: Learning Deep State-Space Models Deep State Space Models for Time Series Forecasting

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:19.864651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 543e8646-50b6-4ebe-9dec-87e1c8343566 · outbound

This paper cites Rauch, Fang-Wu Tung, and Charlotte T.

Latent Matters: Learning Deep State-Space Models Rauch, Fang-Wu Tung, and Charlotte T

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.020359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e676ff6a-8213-4c37-87dd-9ed0d568a73b · outbound

This paper cites Taming VAEs.

Latent Matters: Learning Deep State-Space Models Taming VAEs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.207332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2db83faa-d226-4b25-b2f2-876d90b41c47 · outbound

This paper cites Stochastic backpropagation and approximate inference in deep generative models.ICML, 2014.

Latent Matters: Learning Deep State-Space Models Stochastic backpropagation and approximate inference in deep generative models.ICML, 2014

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.294328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22709713-d24e-4ea1-9335-f2582ef18b34 · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent networks.International Journal of Forecasting, 2020.

Latent Matters: Learning Deep State-Space Models Deepar: Probabilistic forecasting with autoregressive recurrent networks.International Journal of Forecasting, 2020

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.361415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 788b4d78-e65c-42be-8092-5220d3f1efba · outbound

This paper cites DeepMind Control Suite.

Latent Matters: Learning Deep State-Space Models DeepMind Control Suite

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.447308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ee59761-25e5-41af-8fa1-39f37f1744ff · outbound

This paper cites V AE with a VampPrior.

Latent Matters: Learning Deep State-Space Models V AE with a VampPrior

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.540081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13a7165e-1317-469f-bd3d-4b2d108ec074 · outbound

This paper cites Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images.

Latent Matters: Learning Deep State-Space Models Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.602817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6705e2ae-ce86-4d68-bd13-e343ddf2c910 · outbound

This paper cites logq ϕ(z1:T |x 1:T ,u 1:T )−logp ψ0 (z1)− TX t=2 logp ψ(zt|z t−1,u t−1) # (22) ≤E qϕ(z1:T |x 1:T ,u1:T ).

Latent Matters: Learning Deep State-Space Models logq ϕ(z1:T |x 1:T ,u 1:T )−logp ψ0 (z1)− TX t=2 logp ψ(zt|z t−1,u t−1) # (22) ≤E qϕ(z1:T |x 1:T ,u1:T )

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T20:40:20.697672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.