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Paper Citation Record · LEDGER

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems

As of 21 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2607.19628.

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

pith.paper-citation-record.v1
2607.19628 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:16:15.283328Z

measured 66 of 66 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

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Source: cited_works

Reference resolution

66 of 66 outbound references displayed

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  • verified fuzzy0
  • unresolved66
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 0686d5cb-7e55-4eff-bdfa-2b095f07c0d3 · outbound

This paper cites Optimal Control of Partial Differential Equations.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Optimal Control of Partial Differential Equations

Reference 1

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Observation 7c260ed2-a519-411f-be2b-3852a105470d · outbound

This paper cites an unresolved cited work.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Unresolved cited work

Reference 2

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Observation 42ad2392-90b0-4448-aa8d-976d160d9914 · outbound

This paper cites Fleming and H.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Fleming and H

Reference 3

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Observation 06e3e0fe-ef36-4f83-963d-d3531b623c4a · outbound

This paper cites Sutton and Andrew G.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Sutton and Andrew G

Reference 4

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Observation 5a671d0d-f7bc-44e7-8ea4-9f2860aaff52 · outbound

This paper cites Bertsekas and John N.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Bertsekas and John N

Reference 5

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Observation b1451670-53fd-4382-a74e-d29d1f81ff0f · outbound

This paper cites an unresolved cited work.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Unresolved cited work

Reference 6

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Observation 6f6b4afc-340f-45a2-924a-20894c53f44e · outbound

This paper cites Deep reinforcement learning: A brief survey.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Deep reinforcement learning: A brief survey

Reference 7

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Observation feeb43c0-c89c-4dd0-8d11-d1bfdd8d588c · outbound

This paper cites Bellemare, and Joelle Pineau.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Bellemare, and Joelle Pineau

Reference 8

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Observation 92c3a7f5-83e2-421d-9c7a-10c7dfdf8c6a · outbound

This paper cites Human-level control through deep reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Human-level control through deep reinforcement learning

Reference 9

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Observation 6af5490a-ec3f-4d8b-89ba-31b9aa11f4c7 · outbound

This paper cites Mastering complex control in moba games with deep reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Mastering complex control in moba games with deep reinforcement learning

Reference 10

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Observation 4ad93362-8e30-49ee-9ce5-326630161dac · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Playing Atari with Deep Reinforcement Learning

Reference 11

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source=pdf_text observed=2026-08-01T12:16:08.195533Z digest=sha256:9f7bb96b7b53b233d8584bf9cd2ea5333fda87b421577f22922811539b9d36bf

Observation e4eb16a3-69c0-417d-8fcb-6143e39dc037 · outbound

This paper cites Deep reinforcement learning with double q-learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Deep reinforcement learning with double q-learning

Reference 12

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Observation bb652059-cde2-4aa5-ab8f-9a59aa60f370 · outbound

This paper cites Reinforcement learning for robots using neural networks.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Reinforcement learning for robots using neural networks

Reference 13

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Observation 7ce96309-f9ca-4d14-a39a-eb24f466ea41 · outbound

This paper cites Andrew Bagnell, and Jan Peters.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Andrew Bagnell, and Jan Peters

Reference 14

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Observation 21a829e5-c87a-44c7-aae5-45c18664088d · outbound

This paper cites Towards vision-based deep reinforcement learning for robotic motion control.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Towards vision-based deep reinforcement learning for robotic motion control

Reference 15

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Observation f1c97c2d-a894-42c4-8479-fd4e40ef0b6f · outbound

This paper cites Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates

Reference 16

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Observation 064ff056-cea0-4d04-a801-b629d07f61f5 · outbound

This paper cites Sim-to-real transfer in deep reinforcement learning for robotics: a survey.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Sim-to-real transfer in deep reinforcement learning for robotics: a survey

Reference 17

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Observation 20f95b64-7545-4122-a1a1-0650b41fa5ab · outbound

This paper cites Low dimensional state representation learning with robotics priors in continuous action spaces.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Low dimensional state representation learning with robotics priors in continuous action spaces

Reference 18

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Observation 1b4cad3a-969c-4d0a-b7d7-8bc731c7d458 · outbound

This paper cites Control of chaotic systems by deep reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Control of chaotic systems by deep reinforcement learning

Reference 19

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Observation 5b8fd41c-3ee5-45c2-aa67-d34e2a9b1b9f · outbound

This paper cites Reinforcement learning for bluff body active flow control in experiments and simulations.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Reinforcement learning for bluff body active flow control in experiments and simulations

Reference 20

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Observation 26f94feb-60dd-41bb-aa15-a22116ab9d21 · outbound

This paper cites Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach

Reference 21

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Observation 93b83026-4ac7-4ffe-850e-a70b04f2a8b3 · outbound

This paper cites Active flow control for bluff body drag reduction using reinforcement learning with partial measurements.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Active flow control for bluff body drag reduction using reinforcement learning with partial measurements

Reference 22

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Observation 91f66401-f20f-491f-a4c0-fff9518df2ef · outbound

This paper cites Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning

Reference 23

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Observation 416652ab-5202-4acf-a08f-980f95b10cc1 · outbound

This paper cites SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning

Reference 24

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Observation 195bbfa7-bbf4-45bc-9b3f-bbbce9f612f1 · outbound

This paper cites Parametric PDE Control with Deep Reinforcement Learning and L <sub>0</sub> Sparse Polynomial Policies.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Parametric PDE Control with Deep Reinforcement Learning and L <sub>0</sub> Sparse Polynomial Policies

Reference 25

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Observation 571d1375-ba70-4570-acc2-fd4e9656545e · outbound

This paper cites HypeMARL: Multi- Agent Reinforcement Learning For High-Dimensional, Parametric, and Distributed Systems.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems HypeMARL: Multi- Agent Reinforcement Learning For High-Dimensional, Parametric, and Distributed Systems

Reference 26

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Observation b9220098-34de-43bb-b2de-4b17052ebb1e · outbound

This paper cites Implementation matters in deep rl.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Implementation matters in deep rl

Reference 27

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Observation cf74b94c-5bc6-415f-98bd-b4cda89a357e · outbound

This paper cites EPOpt: Learning Robust Neural Network Policies Using Model Ensembles.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

Reference 28

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Observation c69926f4-b6a4-48a9-9b22-a4677fb03b65 · outbound

This paper cites Challenges of Real-World Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Challenges of Real-World Reinforcement Learning

Reference 29

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Observation f9976255-2990-4984-8b49-a0f0c397a2da · outbound

This paper cites Deep reinforcement learning at the edge of the statistical precipice.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Deep reinforcement learning at the edge of the statistical precipice

Reference 30

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Observation 02e8dae2-8c12-4006-b456-62cba3ef9de7 · outbound

This paper cites Assessing Generalization in Deep Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Assessing Generalization in Deep Reinforcement Learning

Reference 31

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Observation ef17d0c1-1ed7-4fd3-922f-19bbf0618342 · outbound

This paper cites Crossing the reality gap: A survey on sim-to-real transferability of robot controllers in reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Crossing the reality gap: A survey on sim-to-real transferability of robot controllers in reinforcement learning

Reference 32

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Observation fbcc7291-354b-44f8-b954-992f5b24ea76 · outbound

This paper cites An empirical investigation of the challenges of real-world reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems An empirical investigation of the challenges of real-world reinforcement learning

Reference 33

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Observation f217aba7-8acf-4dd6-9edf-c5f75d82e390 · outbound

This paper cites Aleatoric and epistemic uncertainty in machine learning: An introduc- tion to concepts and methods.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Aleatoric and epistemic uncertainty in machine learning: An introduc- tion to concepts and methods

Reference 34

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Observation b70add5b-851a-4fe6-9b92-60e89302eeb4 · outbound

This paper cites Uncertainty-aware reinforcement learning agents for noisy environments.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Uncertainty-aware reinforcement learning agents for noisy environments

Reference 35

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Observation bc38f21a-bb63-4be8-899e-c4fc375be9b1 · outbound

This paper cites Masksembles for Uncertainty Estimation.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Masksembles for Uncertainty Estimation

Reference 36

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Observation 36fa8fef-e768-49ee-95f7-285652da9b03 · outbound

This paper cites an unresolved cited work.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Unresolved cited work

Reference 37

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Observation ac9454bb-456b-47ff-8a55-7a896739ffcf · outbound

This paper cites Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning

Reference 38

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Observation c01fe666-3a2f-429c-8ccd-9862ec3e5a90 · outbound

This paper cites Hyperl: Hypernetwork-based reinforcement learning for control of parametrized dynamical systems.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Hyperl: Hypernetwork-based reinforcement learning for control of parametrized dynamical systems

Reference 39

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Observation bfcc7993-2d7a-41cc-b863-d09a2e59d271 · outbound

This paper cites HyperNetworks.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems HyperNetworks

Reference 40

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Observation 9b55948d-b140-4d70-8d14-4f4907a70f0b · outbound

This paper cites A Brief Review of Hypernetworks in Deep Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems A Brief Review of Hypernetworks in Deep Learning

Reference 41

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Observation 2a1ccffb-e9d4-452f-93bc-9e6f0cda9e1b · outbound

This paper cites an unresolved cited work.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Unresolved cited work

Reference 42

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Observation 1994bad7-a6ff-4677-a87a-8a8e9117c67a · outbound

This paper cites Hypernetworks in meta- reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Hypernetworks in meta- reinforcement learning

Reference 43

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Observation 34aa6c25-0bb6-464f-8c33-0bce3fe1cea0 · outbound

This paper cites Bayesian Hypernetworks.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Bayesian Hypernetworks

Reference 44

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Observation be0b92a7-bf83-48f2-84b7-47b70a65890d · outbound

This paper cites Puterman.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Puterman

Reference 45

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Observation 6b5ef0c3-f265-44dd-9087-55d72692bfec · outbound

This paper cites Bertsekas.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Bertsekas

Reference 46

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Observation d71fd274-099e-4b06-a9fd-bf6fee69953a · outbound

This paper cites Mastering atari, go, chess and shogi by planning with a learned model.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Mastering atari, go, chess and shogi by planning with a learned model

Reference 47

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Observation fe921aa0-fafa-459b-b0e1-c55a855ee45e · outbound

This paper cites Model-Based Reinforcement Learning for Atari.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Model-Based Reinforcement Learning for Atari

Reference 48

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Observation c93b2799-061f-49fd-915a-b7ebdba9f95f · outbound

This paper cites Moerland, Joost Broekens, Aske Plaat, and Catholijn M.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Moerland, Joost Broekens, Aske Plaat, and Catholijn M

Reference 49

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Observation 04296ae2-45ed-448b-9c1b-2e00de0501fb · outbound

This paper cites an unresolved cited work.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Unresolved cited work

Reference 50

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Observation a772ee5d-c539-4d5d-a8ee-ca40148d0fef · outbound

This paper cites Konda and John N.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Konda and John N

Reference 51

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Observation a71d499e-36a7-4f3b-8b20-993aaa0057a7 · outbound

This paper cites Addressing function approximation error in actor-critic methods.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Addressing function approximation error in actor-critic methods

Reference 52

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Observation 7795942c-bb59-4e4b-8df6-6e07df0343d9 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 53

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Observation 09c4a2ea-ca0d-42d4-b385-d5d1ae55e4d6 · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 54

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Observation d63c0197-3436-46b2-821d-c1fb36fd4af3 · outbound

This paper cites Addressing function approximation error in actor-critic methods.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Addressing function approximation error in actor-critic methods

Reference 55

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Observation c16fac71-c7f6-43f4-83c4-2b030d553668 · outbound

This paper cites Sutton and Andrew G.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Sutton and Andrew G

Reference 56

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Observation 9425f308-bae0-4e3a-82df-d9a314aa5e93 · outbound

This paper cites Continuous control with deep reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Continuous control with deep reinforcement learning

Reference 57

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Observation 6ae09b76-d0da-49d8-9031-369edb5ce2b2 · outbound

This paper cites Deterministic policy gradient algorithms.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Deterministic policy gradient algorithms

Reference 58

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Observation 7579585c-eead-4743-be02-c5c92cf78efe · outbound

This paper cites LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks

Reference 59

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Observation f933a9ae-08fe-4c8b-ad90-49bfc1efee7d · outbound

This paper cites Randomized Prior Functions for Deep Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Randomized Prior Functions for Deep Reinforcement Learning

Reference 60

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Observation 9ddb9b44-1d4c-420d-9d02-61bfa0e51f4c · outbound

This paper cites For sale: State-action representation learning for deep reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems For sale: State-action representation learning for deep reinforcement learning

Reference 61

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Observation a50334ca-f917-441f-92cd-d91444149501 · outbound

This paper cites Kudryashov.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Kudryashov

Reference 62

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source=pdf_text observed=2026-08-01T12:16:14.808900Z digest=sha256:6264f3863c940c5a92be8fcaef8fb0485af411d55bd12c21d30e635d2ef7b820

Observation f61980ca-3257-4c3b-8038-5c185ffc9d68 · outbound

This paper cites Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning

Reference 63

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source=pdf_text observed=2026-08-01T12:16:14.966360Z digest=sha256:2d3d36282fa30635a8d891d2540419ad1a9e48a6769712b8593b24c09c422b0d

Observation 5b2304bf-9d38-47aa-92a2-86401b4ed93c · outbound

This paper cites Learning efficient navigation in vortical flow fields.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Learning efficient navigation in vortical flow fields

Reference 64

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source=pdf_text observed=2026-08-01T12:16:15.060826Z digest=sha256:8c6425e59b4e701200b5a537cd5355b65a1085b853f85b402e8c82a30acfd361

Observation 4478aa8e-5e07-46c3-b098-8be43c1d33e2 · outbound

This paper cites Finite time lyapunov exponent analysis of model predictive control and reinforcement learning.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems Finite time lyapunov exponent analysis of model predictive control and reinforcement learning

Reference 65

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source=pdf_text observed=2026-08-01T12:16:15.186862Z digest=sha256:896a2026e1027f20f1a9e9c5e518732f71fa8c22f5eb36156f26a47f1de29740

Observation 34891815-80e2-401a-a95f-b30f329d92dd · outbound

This paper cites A novel mechanism for mechanosensory-based rheotaxis in larval zebrafish.

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems A novel mechanism for mechanosensory-based rheotaxis in larval zebrafish

Reference 66

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source=pdf_text observed=2026-08-01T12:16:15.283328Z digest=sha256:74e2d3f39aed536184b9679b6addf723c0a463dbc938dde40d131540e1502215

Pith citing papers

No inbound Pith citation observations are available.