Pith. sign in

Paper Citation Record · LEDGER

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery

As of 14 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2412.07544.

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

pith.paper-citation-record.v1
2412.07544 v2

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:53:41.056882Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

54 of 54 outbound references displayed

  • verified exact3
  • verified fuzzy43
  • unresolved7
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9c00bbd3-8eb1-41f0-9cd5-d6e57407a0a8 · outbound

This paper cites write newline.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T18:53:38.338862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:53:38.338862Z digest=sha256:2939a7db384cbc27a6f39ace191356919fbff703df5417f898c62118a6548210

Observation 9c80e981-5681-4863-81f3-474624d41e64 · outbound

This paper cites Apprenticeship learning via inverse reinforcement learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Apprenticeship learning via inverse reinforcement learning

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.337330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.346152Z digest=sha256:553d9b4bff7daeb93cc2d1686af8087bc8141835ff0b19637ac10fcb1e577b6b

Observation a89f36a0-8c23-43fb-9def-f20a809d328d · outbound

This paper cites Learning L yapunov-stable polynomial dynamical systems through imitation.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning L yapunov-stable polynomial dynamical systems through imitation

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.312515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.474836Z digest=sha256:91b26d2dfe0bc1abbaa077a24489d7e89d8824274ff5799297dbdb283d01322b

Observation b79cf654-879c-4d90-be81-e813c25c2124 · outbound

This paper cites Globally stable neural imitation policies.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Globally stable neural imitation policies

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.284750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.514186Z digest=sha256:fd2d56f2b079c2ecc3e8428d783fbf53fac3f87ce6bbb3c4eb97c49aea8a3a4b

Observation fda7caea-1fec-423b-9c57-4f072a7a572d · outbound

This paper cites Neural dynamic policies for end-to-end sensorimotor learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Neural dynamic policies for end-to-end sensorimotor learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.240586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.534755Z digest=sha256:7dd75f0c8354018ac021b08e595c8d1280ec9da9a7c650d7a96c31ecf8cd8364

Observation 4612988b-9f4f-4a0e-88e8-6afba5de4e48 · outbound

This paper cites Learning stable dynamical systems using contraction theory.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning stable dynamical systems using contraction theory

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.208496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.567879Z digest=sha256:e905cbe84ab9dd2a1813ce54fa603df602314b66962039a7306a728b53557112

Observation 20694a11-1203-43e3-bd68-9b22d0b5e033 · outbound

This paper cites A unified framework for walking and running of bipedal robots.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery A unified framework for walking and running of bipedal robots

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.174594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.590565Z digest=sha256:8b12d773c28db9f9bfff7ac9d1208b1a2e8c1705b7dcb8e5c698879be4307478

Observation cb27f5c3-39cf-475d-bfec-2ba7eab61dab · outbound

This paper cites A PAC-Bayesian Framework for Optimal Control with Stability Guarantees.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery A PAC-Bayesian Framework for Optimal Control with Stability Guarantees

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:53:42.002080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.626027Z digest=sha256:22b109c34a6215f2f2db118acfe5eb11c1b9d37c93de37c0ba2b4eaa86daf522

Observation 0828493a-9e5a-4444-ba1b-7b71b61f857e · outbound

This paper cites Neural ordinary differential equations.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Neural ordinary differential equations

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.154037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.644747Z digest=sha256:aeedefb6309c62f5957bdd7b51969fe2b59bb533b89cde17cae1f052771edd75

Observation 7b4c3484-6fdf-43ce-b314-d96e18aaa7cc · outbound

This paper cites Diffusion policy: V isuomotor policy learning via action diffusion.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Diffusion policy: V isuomotor policy learning via action diffusion

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.111772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.663576Z digest=sha256:160a48e1fc7b62008bac2b860001b494d7dec3a778d0de778675ec826cac165b

Observation 23bc5a61-7caf-4786-9a86-f08aa5f3034b · outbound

This paper cites Soft- DTW : a differentiable loss function for time-series.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Soft- DTW : a differentiable loss function for time-series

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.068015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.675895Z digest=sha256:2e1a455a37c98052addf7c8c3886a41428cd5ace25847c7485e7d88b2157acfe

Observation 47dbb50b-f4e7-4642-b524-1d535ffa2be6 · outbound

This paper cites Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.053668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.710113Z digest=sha256:5067a65ca2c52c288117fbe9ef219243baf8b6fbb5514b7e0d0790d5e9fcf170

Observation 5b8d4fda-5c4c-44d1-9dc5-e66f8fe7183b · outbound

This paper cites An introduction to chaotic dynamical systems.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery An introduction to chaotic dynamical systems

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:46.028522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.741902Z digest=sha256:3f86076d38ee4b1a1b82e8a0a2efbc6b2f99055700e4d83186be10966a36988c

Observation bf99ce67-20c7-47c7-9017-107a24a1ef47 · outbound

This paper cites Density estimation using real NVP.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Density estimation using real NVP

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T18:53:38.773155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:53:38.773155Z digest=sha256:1ae7cf3bd6a028b461aaac364962b787687ff3ea482eb350502a4d4a68760a7d

Observation 30303fc8-0b96-4ab4-add2-5a4aaaf1b7da · outbound

This paper cites A physically-consistent bayesian non-parametric mixture model for dynamical system learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery A physically-consistent bayesian non-parametric mixture model for dynamical system learning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.858612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:38.950419Z digest=sha256:b12e702aadc86648c67352ec57a0b9e6a8bb20b0edbae5a10bbea589c5f053dc

Observation 8fcc510d-e488-43b0-90e8-1d3b1a8caff3 · outbound

This paper cites Learning robust rewards with adversarial inverse reinforcement learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning robust rewards with adversarial inverse reinforcement learning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.772412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.051776Z digest=sha256:8e6c89970cf7d416c38a12b5e4195a91b079866df4694bd0efc2b99e2626a789

Observation 01e31d17-b963-4c42-a0bd-74c3d1ad00d6 · outbound

This paper cites Generative adversarial imitation learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Generative adversarial imitation learning

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.744816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.113474Z digest=sha256:0631a48ed53dff409b734fd83bb74445df2cfd56877eac4fde0fed589044a48d

Observation 0fec38dd-c4c7-4124-a0ae-5218133c62b9 · outbound

This paper cites Imitation learning: A survey of learning methods.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Imitation learning: A survey of learning methods

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.716099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.123013Z digest=sha256:9210863a70f834ea3db2a710e6da34ffae89310a205a92db46bf4af20f02dee3

Observation 02c33aad-7d1d-4334-a015-33aed9417b96 · outbound

This paper cites Exact indexing of dynamic time warping.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Exact indexing of dynamic time warping

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.546477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.131238Z digest=sha256:4f13e893c2e8a7c5f52aafba1f6a08292123844812803d616de574237b409e3a

Observation fb926238-e745-4347-9254-6067146fd196 · outbound

This paper cites Learning stable nonlinear dynamical systems with G aussian mixture models.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning stable nonlinear dynamical systems with G aussian mixture models

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.384855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.230170Z digest=sha256:c9d4e0f8edbfcbbbdfe8fd5aed40238532dff0fbd344ebc0aa1176d8a9dbd944

Observation e7db9b90-0e38-41c7-b5bc-f28e1bfec97a · outbound

This paper cites Learning control L yapunov function to ensure stability of dynamical system-based robot reaching motions.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning control L yapunov function to ensure stability of dynamical system-based robot reaching motions

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.301498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.265033Z digest=sha256:5b97b2e223c419dc77c1007ff0b6fb0a68d8963b63ca1e719ffdf2a1f5df067a

Observation d2dde37e-4cfe-42ef-86dd-42974ee0cd21 · outbound

This paper cites Learning stable deep dynamics models.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning stable deep dynamics models

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.247732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.286321Z digest=sha256:e49cb7c0938e2873c1fcb70090822240bc78013ce092201157008552b6a03b58

Observation 574a3d89-0f32-403a-a893-2a17cd03423a · outbound

This paper cites D ART : Noise injection for robust imitation learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery D ART : Noise injection for robust imitation learning

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.186405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.368079Z digest=sha256:361c4ae0fdb63ece86f1fea85fcd4903ab655984089cac91fe531fd4c8abd35f

Observation dcbf1594-09d6-4517-95db-3af0dd19f60d · outbound

This paper cites an unresolved cited work.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:53:45.051017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.435065Z digest=sha256:04d90d19e2eea079c7c33ab1c5763c0b679ef3508384820a1274c0223c88756c

Observation 58ae07f3-fa06-438e-b39b-4b9a9240e0dc · outbound

This paper cites Manchester and Jean-Jacques E.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Manchester and Jean-Jacques E

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:45.014763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.544110Z digest=sha256:f6c65ca96d587ab92ad1a19dcd020c89d9c2f0e57520fb58ed8c66c182621a1d

Observation 54126d8f-0fc8-44c4-9968-2d246b917e8a · outbound

This paper cites GTI: Learning to Generalize across Long-Horizon Tasks from Human Demonstrations.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery GTI: Learning to Generalize across Long-Horizon Tasks from Human Demonstrations

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.820537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.556394Z digest=sha256:62f7de0991170f1f9bd5b2f3a937ed502805e8a345d4e1a40ddc90888bd326e0

Observation 0fc0dbec-d16d-4ed9-af24-07e89d89c7c7 · outbound

This paper cites What matters in learning from offline human demonstrations for robot manipulation.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery What matters in learning from offline human demonstrations for robot manipulation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.754487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.565549Z digest=sha256:5df141c63d05f03aee01390d70067f4647747464fc1789a6ef71b755a3a79984

Observation 57e4eadd-dc28-4998-8aa3-31c9f2510f74 · outbound

This paper cites Learning to optimize with convergence guarantees using nonlinear system theory.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning to optimize with convergence guarantees using nonlinear system theory

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.700008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.604972Z digest=sha256:46de3b960d499dfc6602e070ad477fe0c7bba73fd6b2552df3866f17bd491373

Observation 90091cd0-f3ca-40f3-a2f1-d69ab06276f0 · outbound

This paper cites Manchester, Luca Furieri, and Giancarlo Ferrari-Trecate.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Manchester, Luca Furieri, and Giancarlo Ferrari-Trecate

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.504898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.626069Z digest=sha256:9026f4e542c30b8227dde607207d728efc2319b9d387d762a7f396b83bca5d8d

Observation 95b7c21e-6751-42dd-ba49-a47edb61c739 · outbound

This paper cites Kochenderfer.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Kochenderfer

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.434761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.637663Z digest=sha256:d0f9cfc77edda169e4ad12816c271f375b6c1a6facd0f55bdfc30e484396658a

Observation ff65ba56-19bc-4c48-968e-99867394651a · outbound

This paper cites Orbit: A unified simulation framework for interactive robot learning environments.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Orbit: A unified simulation framework for interactive robot learning environments

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.235804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.647140Z digest=sha256:9ce26fc3d7b503394b8ed565d582cbcc63971f567a852b478092e57381d36dd1

Observation 9d7709d7-2ce6-4769-a9b8-b53a233a841f · outbound

This paper cites Neural contractive dynamical systems.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Neural contractive dynamical systems

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.134751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.703987Z digest=sha256:afe394db5958328ed2c35a2c35bffb040e5d6228013d27a426357d2af9d21f84

Observation 2b52a254-adc0-4da8-add6-fa04b086fca7 · outbound

This paper cites Learning robot motions with stable dynamical systems under diffeomorphic transformations.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning robot motions with stable dynamical systems under diffeomorphic transformations

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.927026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.776028Z digest=sha256:8f7dfc10ccb2f97404096e81da25d8befc6db1ed9c1b5f15ec6ff05c373803f5

Observation fcb830ba-6fbf-4d0c-bdb9-6efdb792d1b0 · outbound

This paper cites Normalizing flows for probabilistic modeling and inference.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Normalizing flows for probabilistic modeling and inference

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T18:53:39.874762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:53:39.874762Z digest=sha256:4050044e95225edce048061631ab18a0afeb3ee0e82f2e28a7b60b849c2076d2

Observation e0d89953-8641-4bae-86ef-e564eb2e2b7c · outbound

This paper cites P y T orch: An imperative style, high-performance deep learning library.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery P y T orch: An imperative style, high-performance deep learning library

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.684752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.911678Z digest=sha256:5142d37b33c18daa81d0bb319ddca6c95ad028b38fbbcdab480980dfd8d44b77

Observation 94f9d5d4-420e-4f86-9213-114ff6638bce · outbound

This paper cites Variational discriminator bottleneck: Improving imitation learning, inverse RL , and GAN s by constraining information flow.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Variational discriminator bottleneck: Improving imitation learning, inverse RL , and GAN s by constraining information flow

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.544755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.930966Z digest=sha256:7b47c152f168f425d461e4bb59501e6470431b40196db0bbd8b487c1b171b1a5

Observation 7ee44d76-35e4-40a7-85fc-6293270841cf · outbound

This paper cites an unresolved cited work.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Unresolved cited work

Reference 37

Resolution
verified exact
doi, observed 2026-08-11T18:53:41.281194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.956732Z digest=sha256:66a80ab0af13657e0a72eb81ad9fee53e8281e132d83879b70138aaa3001d105

Observation 68d9906f-8471-4021-8ee7-f7981b2b09cd · outbound

This paper cites ALVINN : An autonomous land vehicle in a neural network.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery ALVINN : An autonomous land vehicle in a neural network

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.440586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:39.996322Z digest=sha256:ab5fbce2826cd40b74ad8ebcf5325145070d89cad37ad1d0252d4144fbebfc99

Observation 3ebb4cae-b5a6-4d69-9154-ef9836f3d6be · outbound

This paper cites Euclideanizing flows: Diffeomorphic reduction for learning stable dynamical systems.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Euclideanizing flows: Diffeomorphic reduction for learning stable dynamical systems

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.374754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.046771Z digest=sha256:1966398e698b492150d5b8d221a5feab2ca2d5dc93ca6c23888e0323beaa562e

Observation 56efa743-d94a-4c17-98f2-5f32dd4b08b0 · outbound

This paper cites Learning partially contracting dynamical systems from demonstrations.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning partially contracting dynamical systems from demonstrations

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.255331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.144894Z digest=sha256:0e039c69b94cf2c65927f9d3f1cd425d46e0dfcd8a0bb61c614ffbe741c81459

Observation 774a1c40-09c3-4348-ae6b-0e7b86246642 · outbound

This paper cites Recent advances in robot learning from demonstration.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Recent advances in robot learning from demonstration

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.114755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.194899Z digest=sha256:6d19b0c722e27df75b4611371fb2e46154f5b7b313311cb8a4729184b1d4c573

Observation 43bb37b2-45f8-4e8c-9347-167edbaa70e4 · outbound

This paper cites Recurrent equilibrium networks: Flexible dynamic models with guaranteed stability and robustness.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Recurrent equilibrium networks: Flexible dynamic models with guaranteed stability and robustness

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.026961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.264750Z digest=sha256:7bd779a7674039fc81388cce772b9528a4665d7a218a8ac67252dc492d3be7c4

Observation 60dd3ded-6819-48da-b9cb-faf89695e2fc · outbound

This paper cites Efficient reductions for imitation learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Efficient reductions for imitation learning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.874756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.336775Z digest=sha256:1a8fee7916577b4b233ad5b482602ad788d2b8a4949bd4b81e08108daabd85b3

Observation 16fbb832-ee89-4a79-8ace-04e4cd4c2544 · outbound

This paper cites Learning Contracting Vector Fields For Stable Imitation Learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning Contracting Vector Fields For Stable Imitation Learning

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:53:41.775351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.434128Z digest=sha256:fed1b8f1eaf44d9964549b0dece46fab46564cc297ca66c5ae76e32fb4042cdc

Observation 030e439b-c94d-4072-8b51-7a6e29912ac2 · outbound

This paper cites Learning deep dynamical systems using stable neural O D E s.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning deep dynamical systems using stable neural O D E s

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.717625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.496461Z digest=sha256:ae819b7b165a1394828096e9f44947d9f3cabb75462f6c89b9f469345f098ed2

Observation 9323731b-3167-4567-93d6-3553d8d5b1cd · outbound

This paper cites A family of nonparametric density estimation algorithms.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery A family of nonparametric density estimation algorithms

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.693460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.608481Z digest=sha256:5e7fbe219ec86594ec54143d4ecbc5d8c8c8ce97340a470c0d2a063f39f692d5

Observation b91445a3-ea41-4af2-8e13-52e94dc78008 · outbound

This paper cites Behavioral cloning from observation.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Behavioral cloning from observation

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.651403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.723041Z digest=sha256:29f08773a288eb2c2c6451902e1f4cb0a12caac5f24f8a384af35c066e863b98

Observation 574123c3-579c-4688-83bb-454ee55c6ad1 · outbound

This paper cites Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.499298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.755411Z digest=sha256:a47c10520685919184fb8b5897d5c53c55c1ad5b3f930b237b78d40733803c4e

Observation 1413f81b-a838-46c7-af17-01cc752091ec · outbound

This paper cites an unresolved cited work.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:53:42.400954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.794767Z digest=sha256:d1270353324ea7f4d434b23362e8d7e39363ff0211605d4731d2caee3d4cd017

Observation 4bc5c14f-135a-4bcd-a7d8-9a9e964fd0e4 · outbound

This paper cites Learning R iemannian stable dynamical systems via diffeomorphisms.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Learning R iemannian stable dynamical systems via diffeomorphisms

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.292011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.848455Z digest=sha256:c264ccd0700e92002e73259dfeab9330e64d7e1fc9cbeed9aa06fb323745ff1e

Observation 3be31258-02c9-4608-9d6d-935d22a14135 · outbound

This paper cites Maximum entropy inverse reinforcement learning.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Maximum entropy inverse reinforcement learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:42.172253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:53:40.951815Z digest=sha256:a68e92e76f12f7b66ed96610d675c938171cf3f063eece0e9d9cbe9c39463b09

Observation a006eb8f-d7ee-4d9f-9d94-ea2cc54118e1 · outbound

This paper cites @esa (Ref.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery @esa (Ref

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T18:53:41.017028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:53:41.017028Z digest=sha256:11ecbf8160e172533b2bca70fb43a07ba9cf71c059349a13cb3a76b7b2212afe

Observation 174d4559-01be-4306-9377-28a9e16a77cf · outbound

This paper cites an unresolved cited work.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Unresolved cited work

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T18:53:41.038755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:53:41.038755Z digest=sha256:cc2fb37b25216a846a7d1fc5615626a7369d7d7601f9a358db0f4ab0613d6cc3

Observation d0dc93d6-dc86-4dd8-88a3-7d80ee5605f0 · outbound

This paper cites Lift”, “Can.

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery Lift”, “Can

Reference 54

Resolution
malformed identifier
no resolver link, observed 2026-08-11T18:53:41.056882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:53:41.056882Z digest=sha256:8075a0c1032a5b9b9fef4c834637b7461c6c24e1f6797b36ad38a25a5d0fe2b2

Pith citing papers

No inbound Pith citation observations are available.