Paper Citation Record · LEDGER

Wasserstein Policy Optimization

As of 17 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 5 inbound Pith citation observations for arXiv:2505.00663.

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

pith.paper-citation-record.v1
2505.00663 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:47:05.795761Z

measured 59 of 59 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T22:19:53.934535Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T06:56:44.503712Z

Reference resolution

54 of 54 outbound references displayed

verified exact3
verified fuzzy22
unresolved29
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b5b7dfde-d8ef-4053-a00f-f73925c912b2 · outbound

This paper cites write newline.

Wasserstein Policy Optimization write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.588081Z

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Observation 2254d3da-e420-4c79-b6aa-9e78c980eec9 · outbound

This paper cites T., Tassa, Y., Munos, R., Heess, N., and Riedmiller, M.

Wasserstein Policy Optimization T., Tassa, Y., Munos, R., Heess, N., and Riedmiller, M

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.331926Z

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Observation 5ab9bc6b-cab4-4dbc-b48b-8645b4b1b909 · outbound

This paper cites Wasserstein Robust Reinforcement Learning.

Wasserstein Policy Optimization Wasserstein Robust Reinforcement Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.597189Z

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Observation 733ba229-d450-4089-88ae-ba561c450cbc · outbound

This paper cites M., Lee, J.

Wasserstein Policy Optimization M., Lee, J

Reference 4

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Observation d34dd838-1579-4ca8-aba0-b935f4832c21 · outbound

This paper cites Gradient flows: in metric spaces and in the space of probability measures.

Wasserstein Policy Optimization Gradient flows: in metric spaces and in the space of probability measures

Reference 5

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Observation 56df3e18-0b0e-4184-b5d8-f649980ff82f · outbound

This paper cites W., Budden, D., Dabney, W., Horgan, D., Tb, D., Muldal, A., Heess, N., and Lillicrap, T.

Wasserstein Policy Optimization W., Budden, D., Dabney, W., Horgan, D., Tb, D., Muldal, A., Heess, N., and Lillicrap, T

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.306496Z

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

Observation 41dad690-926f-4135-b459-184cc07b59cb · outbound

This paper cites G., Sutton, R.

Wasserstein Policy Optimization G., Sutton, R

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.294957Z

Source-reported events for the cited work

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

Observation c109af0b-e5a3-41d2-a497-fa0e246179c5 · outbound

This paper cites G., Dabney, W., and Munos, R.

Wasserstein Policy Optimization G., Dabney, W., and Munos, R

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.283686Z

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Observation 9662de86-3d7e-48cc-930a-e1e12a352561 · outbound

This paper cites and Brenier, Y.

Wasserstein Policy Optimization and Brenier, Y

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.619989Z

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Observation d8ac57cd-5b35-4274-82fb-516c7af50691 · outbound

This paper cites Development of free-boundary equilibrium and transport solvers for simulation and real-time interpretation of tokamak experiments.

Wasserstein Policy Optimization Development of free-boundary equilibrium and transport solvers for simulation and real-time interpretation of tokamak experiments

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.266647Z

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Observation 59307d2d-0cea-46e5-806f-be758d7ddaf0 · outbound

This paper cites MICo: Improved representations via sampling-based state similarity for Markov decision processes.

Wasserstein Policy Optimization MICo: Improved representations via sampling-based state similarity for Markov decision processes

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.628603Z

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Observation 5b4cddc1-b794-4c27-9d69-bffcd7d184c8 · outbound

This paper cites T., Rubanova, Y., Bettencourt, J., and Duvenaud, D.

Wasserstein Policy Optimization T., Rubanova, Y., Bettencourt, J., and Duvenaud, D

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.634035Z

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Observation c38ecf22-afac-4732-8aba-d3fcf077b551 · outbound

This paper cites Fast and accurate deep network learning by exponential linear units (elus).

Wasserstein Policy Optimization Fast and accurate deep network learning by exponential linear units (elus)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.248832Z

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Observation 6f464a34-6fdf-406c-87b2-0e9a0a2d4222 · outbound

This paper cites Magnetic control of tokamak plasmas through deep reinforcement learning.

Wasserstein Policy Optimization Magnetic control of tokamak plasmas through deep reinforcement learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.642253Z

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Observation 0495d737-0898-4b96-bce4-c7eec5c1cbae · outbound

This paper cites Experimental research on the TCV tokamak.

Wasserstein Policy Optimization Experimental research on the TCV tokamak

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.645704Z

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Observation 3a3fc4cf-9920-41a2-b044-ee578f2224fb · outbound

This paper cites Sigmoid-weighted linear units for neural network function approximation in reinforcement learning.

Wasserstein Policy Optimization Sigmoid-weighted linear units for neural network function approximation in reinforcement learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.649683Z

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Observation 2ec59336-bd68-4aaf-a304-ee1b46abba65 · outbound

This paper cites CALE: Continuous Arcade Learning Environment.

Wasserstein Policy Optimization CALE: Continuous Arcade Learning Environment

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:47:05.935740Z

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Observation b7d4ecf8-0e0e-4cbb-b112-33cb32583843 · outbound

This paper cites Metrics for finite markov decision processes.

Wasserstein Policy Optimization Metrics for finite markov decision processes

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.222698Z

Source-reported events for the cited work

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

Observation 6335febe-a02a-473e-9ae8-dedb8a0a42fe · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.

Wasserstein Policy Optimization Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.661528Z

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Observation 27536610-f19e-42b6-8a56-2f38f5d39127 · outbound

This paper cites H., Tirumala, D., Humplik, J., Wulfmeier, M., Tunyasuvunakool, S., Siegel, N.

Wasserstein Policy Optimization H., Tirumala, D., Humplik, J., Wulfmeier, M., Tunyasuvunakool, S., Siegel, N

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.202530Z

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Observation 857f1670-9d4e-432b-99e7-5be13481fc37 · outbound

This paper cites Wasserstein Unsupervised Reinforcement Learning.

Wasserstein Policy Optimization Wasserstein Unsupervised Reinforcement Learning

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:47:05.922391Z

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Observation 744ec0f7-4171-4892-9043-dd086adef2b2 · outbound

This paper cites Learning continuous control policies by stochastic value gradients.

Wasserstein Policy Optimization Learning continuous control policies by stochastic value gradients

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.191434Z

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Observation 2fd903b9-9f74-4b6a-b4c6-bf191014cea0 · outbound

This paper cites Acme: A Research Framework for Distributed Reinforcement Learning.

Wasserstein Policy Optimization Acme: A Research Framework for Distributed Reinforcement Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.678159Z

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Observation 0395637c-0a5c-4c90-9a66-d09ac040974d · outbound

This paper cites an unresolved cited work.

Wasserstein Policy Optimization Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:47:06.177293Z

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Observation 45aaa500-a603-4a85-a431-74aea021f4e5 · outbound

This paper cites an unresolved cited work.

Wasserstein Policy Optimization Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:47:06.165323Z

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Observation b48467e3-ffd7-45c6-a333-91bda38df65b · outbound

This paper cites Categorical reparameterization with G umbel-softmax.

Wasserstein Policy Optimization Categorical reparameterization with G umbel-softmax

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.154538Z

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Observation acc2e2a9-bed6-428e-bb47-9446929ffd68 · outbound

This paper cites an unresolved cited work.

Wasserstein Policy Optimization Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:47:06.142634Z

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Observation 51a4ad7c-dfc5-4b11-af34-2432dd3181ce · outbound

This paper cites Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control.

Wasserstein Policy Optimization Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:47:05.898230Z

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Observation 683d7e2a-d004-4fca-a499-b7fcbeebd1f1 · outbound

This paper cites Continuous control with deep reinforcement learning.

Wasserstein Policy Optimization Continuous control with deep reinforcement learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.706926Z

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Observation fa09afc5-6421-442b-89e4-cf543840fdda · outbound

This paper cites J., Mnih, A., and Teh, Y.

Wasserstein Policy Optimization J., Mnih, A., and Teh, Y

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.130226Z

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Observation 9850b65c-b8ab-4482-8108-b8e4a356824a · outbound

This paper cites and Grosse, R.

Wasserstein Policy Optimization and Grosse, R

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.118288Z

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Observation ac03dda1-012e-4034-95eb-2c6f0a8b5bb0 · outbound

This paper cites M., Likmeta, A., and Restelli, M.

Wasserstein Policy Optimization M., Likmeta, A., and Restelli, M

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.105754Z

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

Observation e144be77-e467-494d-945b-4a65c3f7f94a · outbound

This paper cites Efficient Wasserstein Natural Gradients for Reinforcement Learning.

Wasserstein Policy Optimization Efficient Wasserstein Natural Gradients for Reinforcement Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.722747Z

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Observation afd51786-a8c3-48b1-b167-0d308880fc81 · outbound

This paper cites Wasserstein quantum M onte C arlo: a novel approach for solving the quantum many-body schr \"o dinger equation.

Wasserstein Policy Optimization Wasserstein quantum M onte C arlo: a novel approach for solving the quantum many-body schr \"o dinger equation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.094875Z

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Observation f9fe4337-2e4f-4197-ae50-0dc6f03d9957 · outbound

This paper cites Learning to score behaviors for guided policy optimization.

Wasserstein Policy Optimization Learning to score behaviors for guided policy optimization

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.083773Z

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

Observation 75eb8626-fb33-486c-b607-92acf35b5274 · outbound

This paper cites Revisiting Natural Gradient for Deep Networks.

Wasserstein Policy Optimization Revisiting Natural Gradient for Deep Networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.734888Z

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Observation d6f13103-9698-4474-9d76-bc0048a81deb · outbound

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Wasserstein Policy Optimization Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:47:06.073639Z

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Observation 800c788b-db9b-4b7d-a572-59a67930c74c · outbound

This paper cites an unresolved cited work.

Wasserstein Policy Optimization Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:47:06.063889Z

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Observation 094c430b-f82f-4804-b88c-8209fbf8b329 · outbound

This paper cites Trust region policy optimization.

Wasserstein Policy Optimization Trust region policy optimization

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.054524Z

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Observation e8ff4f7c-2665-4a90-8f0b-8d98c02f2f19 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Wasserstein Policy Optimization High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.750096Z

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Observation 368ea6c0-f820-49db-9008-38cc22728977 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Wasserstein Policy Optimization Proximal Policy Optimization Algorithms

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.753537Z

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Observation 07849974-2fdd-4b13-8a43-d4366ea6a636 · outbound

This paper cites Deterministic policy gradient algorithms.

Wasserstein Policy Optimization Deterministic policy gradient algorithms

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.044687Z

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Observation 49344668-057b-44f7-aa5c-cc03726391f9 · outbound

This paper cites V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control.

Wasserstein Policy Optimization V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.760618Z

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Observation 6dee8b22-00dd-4fd2-953b-4b7fa8930f26 · outbound

This paper cites an unresolved cited work.

Wasserstein Policy Optimization Unresolved cited work

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.763904Z

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Observation e000d2e0-7711-4541-8ec6-49ec0d647327 · outbound

This paper cites S., McAllester, D., Singh, S., and Mansour, Y.

Wasserstein Policy Optimization S., McAllester, D., Singh, S., and Mansour, Y

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.767085Z

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Observation e5e35a59-79ac-48c1-99df-a0c872ebd9c8 · outbound

This paper cites DeepMind Control Suite.

Wasserstein Policy Optimization DeepMind Control Suite

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.770349Z

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Observation f4975490-ef45-488d-9b33-09be25f5bf14 · outbound

This paper cites Mujoco: A physics engine for model-based control.

Wasserstein Policy Optimization Mujoco: A physics engine for model-based control

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.773879Z

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Observation 1b4fa37c-7da9-453d-82ff-66061c19dcde · outbound

This paper cites D., Michi, A., Chervonyi, Y., Davies, I., Paduraru, C., Lazic, N., Felici, F., Ewalds, T., Donner, C., Galperti, C., et al.

Wasserstein Policy Optimization D., Michi, A., Chervonyi, Y., Davies, I., Paduraru, C., Lazic, N., Felici, F., Ewalds, T., Donner, C., Galperti, C., et al

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.776825Z

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Observation 72b0774e-5686-4f6c-81fb-ee1b71650855 · outbound

This paper cites dm\_control: Software and tasks for continuous control.

Wasserstein Policy Optimization dm\_control: Software and tasks for continuous control

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.010833Z

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

Observation 76ec6004-2123-427e-af7e-1944d25931b7 · outbound

This paper cites Double q-learning.

Wasserstein Policy Optimization Double q-learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:06.000229Z

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

Observation 3aa6ab08-bd3a-4050-a7d9-e48c39a41b19 · outbound

This paper cites and Wiering, M.

Wasserstein Policy Optimization and Wiering, M

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:05.989811Z

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

Observation 2014b134-8925-4098-b8d1-a254e7e549b1 · outbound

This paper cites Beyond regression: N ew tools for prediction and analysis in the behavioral sciences.

Wasserstein Policy Optimization Beyond regression: N ew tools for prediction and analysis in the behavioral sciences

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:05.978635Z

Source-reported events for the cited work

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

Observation 7ec0bc46-1d29-498e-8564-414468894dd6 · outbound

This paper cites an unresolved cited work.

Wasserstein Policy Optimization Unresolved cited work

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.792655Z

Source-reported events for the cited work

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Observation 8b443736-3676-4c3d-a32e-2b9135f53f77 · outbound

This paper cites Policy optimization as W asserstein gradient flows.

Wasserstein Policy Optimization Policy optimization as W asserstein gradient flows

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:47:05.962950Z

Source-reported events for the cited work

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

Pith citing papers

Observation ac0cc622-9671-4b93-b2be-8695092a6a38 · inbound

Challenges and opportunities for AI to help deliver fusion energy cites this paper.

Challenges and opportunities for AI to help deliver fusion energy Wasserstein Policy Optimization

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:43:25.441685Z

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

Observation d42fbe4a-6cef-4066-bedb-7edae218c41c · inbound

A note on convergence of Wasserstein policy optimization cites this paper.

A note on convergence of Wasserstein policy optimization Wasserstein Policy Optimization

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:41:10.858631Z

Source-reported events for the cited work

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

Observation 5238f7d7-76f5-44de-b82b-131b8f3d9832 · inbound

Global Convergence of Wasserstein Policy Gradient for Entropy-Regularized Reinforcement Learning cites this paper.

Global Convergence of Wasserstein Policy Gradient for Entropy-Regularized Reinforcement Learning Wasserstein Policy Optimization

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T22:24:00.339861Z

Source-reported events for the cited work

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

Observation 42fb7b7b-e288-4bc2-a5d4-6af7262093e9 · inbound

Ratio-Variance Regularized Policy Optimization cites this paper.

Ratio-Variance Regularized Policy Optimization Wasserstein Policy Optimization

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:53:55.983387Z

Source-reported events for the cited work

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

Observation 2aca0c6c-ab04-45a0-9c52-c2ef9587a81b · inbound

Policy Gradient for Continuous-Time Robust Markov Decision Processes cites this paper.

Policy Gradient for Continuous-Time Robust Markov Decision Processes Wasserstein Policy Optimization

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T06:56:44.505465Z

Source-reported events for the cited work

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