{"total":142,"rows":[{"id":"2104.09459","title":"A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups","created":"2021-04-19","cited_by_count":187,"area":null},{"id":"2205.13209","title":"Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization","created":"2022-05-26","cited_by_count":119,"area":null},{"id":"2211.06489","title":"Equivariance with Learned Canonicalization Functions","created":"2022-11-11","cited_by_count":109,"area":null},{"id":"2112.01388","title":"Residual Pathway Priors for Soft Equivariance Constraints","created":"2021-12-02","cited_by_count":75,"area":null},{"id":"2306.02451","title":"For SALE: State-Action Representation Learning for Deep Reinforcement Learning","created":"2023-06-04","cited_by_count":75,"area":null},{"id":"2204.11371","title":"Learning Symmetric Embeddings for Equivariant World Models","created":"2022-04-24","cited_by_count":54,"area":"wm"},{"id":"2110.14096","title":"Towards Robust Bisimulation Metric Learning","created":"2021-10-27","cited_by_count":49,"area":null},{"id":"2202.10638","title":"Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations","created":"2022-02-22","cited_by_count":42,"area":null},{"id":"2501.16142","title":"Towards General-Purpose Model-Free Reinforcement Learning","created":"2025-01-27","cited_by_count":41,"area":"deeprl"},{"id":"2102.10960","title":"Return-Based Contrastive Representation Learning for Reinforcement Learning","created":"2021-02-22","cited_by_count":36,"area":null},{"id":"2209.08025","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","created":"2022-09-16","cited_by_count":36,"area":null},{"id":"2211.09231","title":"The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry","created":"2022-11-16","cited_by_count":33,"area":null},{"id":"2403.04359","title":"Symmetry Considerations for Learning Task Symmetric Robot Policies","created":"2024-03-07","cited_by_count":28,"area":null},{"id":"2111.01365","title":"Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics","created":"2021-11-02","cited_by_count":27,"area":"offlinerl"},{"id":"2111.04714","title":"A Dataset Perspective on Offline Reinforcement Learning","created":"2021-11-08","cited_by_count":27,"area":"offlinerl"},{"id":"2209.07364","title":"Continuous MDP Homomorphisms and Homomorphic Policy Gradient","created":"2022-09-15","cited_by_count":27,"area":null},{"id":"2203.09250","title":"Symmetry-Based Representations for Artificial and Biological General Intelligence","created":"2022-03-17","cited_by_count":26,"area":null},{"id":"2306.02866","title":"Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance","created":"2023-06-05","cited_by_count":26,"area":null},{"id":"2110.04495","title":"Multi-Agent MDP Homomorphic Networks","created":"2021-10-09","cited_by_count":25,"area":null},{"id":"2403.17320","title":"Leveraging Symmetry in RL-based Legged Locomotion Control","created":"2024-03-26","cited_by_count":25,"area":"deeprl"},{"id":"2405.15369","title":"Cross-Domain Policy Adaptation by Capturing Representation Mismatch","created":"2024-05-24","cited_by_count":25,"area":"deeprl"},{"id":"2310.06131","title":"Learning Layer-wise Equivariances Automatically using Gradients","created":"2023-10-09","cited_by_count":23,"area":null},{"id":"2204.13661","title":"Toward Compositional Generalization in Object-Oriented World Modeling","created":"2022-04-28","cited_by_count":22,"area":"wm"},{"id":"2210.06475","title":"Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models","created":"2022-10-13","cited_by_count":22,"area":null},{"id":"2206.08704","title":"Maximum Class Separation as Inductive Bias in One Matrix","created":"2022-06-17","cited_by_count":21,"area":null},{"id":"2303.04745","title":"A General Theory of Correct, Incorrect, and Extrinsic Equivariance","created":"2023-03-08","cited_by_count":19,"area":null},{"id":"2207.12067","title":"Homomorphism Autoencoder -- Learning Group Structured Representations from Observed Transitions","created":"2022-07-25","cited_by_count":18,"area":null},{"id":"2208.14226","title":"Unsupervised Representation Learning in Deep Reinforcement Learning: A Review","created":"2022-08-27","cited_by_count":18,"area":null},{"id":"2405.13178","title":"One-Shot Imitation Learning with Invariance Matching for Robotic Manipulation","created":"2024-05-21","cited_by_count":18,"area":"offlinerl"},{"id":"2408.14336","title":"Equivariant Reinforcement Learning under Partial Observability","created":"2024-08-26","cited_by_count":18,"area":"deeprl"},{"id":"2210.12124","title":"Equivariant Networks for Zero-Shot Coordination","created":"2022-10-21","cited_by_count":16,"area":null},{"id":"2306.16021","title":"Structure in Deep Reinforcement Learning: A Survey and Open Problems","created":"2023-06-28","cited_by_count":16,"area":null},{"id":"2210.05972","title":"Unsupervised Learning of Equivariant Structure from Sequences","created":"2022-10-12","cited_by_count":15,"area":null},{"id":"2310.12690","title":"Neurosymbolic Grounding for Compositional World Models","created":"2023-10-19","cited_by_count":14,"area":"wm"},{"id":"2306.00036","title":"Symmetry-Aware Robot Design with Structured Subgroups","created":"2023-05-31","cited_by_count":13,"area":null},{"id":"2402.15552","title":"Morphological Symmetries in Robotics","created":"2024-02-23","cited_by_count":13,"area":null},{"id":"2306.06489","title":"On Robot Grasp Learning Using Equivariant Models","created":"2023-06-10","cited_by_count":12,"area":null},{"id":"2305.09900","title":"Efficient Equivariant Transfer Learning from Pretrained Models","created":"2023-05-17","cited_by_count":11,"area":null},{"id":"2305.18951","title":"Subequivariant Graph Reinforcement Learning in 3D Environments","created":"2023-05-30","cited_by_count":11,"area":null},{"id":"2309.13167","title":"Flow Factorized Representation Learning","created":"2023-09-22","cited_by_count":11,"area":null},{"id":"2210.12301","title":"Continual Vision-based Reinforcement Learning with Group Symmetries","created":"2022-10-21","cited_by_count":10,"area":null},{"id":"2310.18247","title":"Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning","created":"2023-10-27","cited_by_count":10,"area":"offlinerl"},{"id":"2410.02581","title":"Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance","created":"2024-10-03","cited_by_count":10,"area":null},{"id":"2502.07005","title":"Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects","created":"2025-02-10","cited_by_count":10,"area":null},{"id":"2503.09829","title":"SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey","created":"2025-03-12","cited_by_count":10,"area":"offlinerl"},{"id":"2305.05666","title":"Policy Gradient Methods in the Presence of Symmetries and State Abstractions","created":"2023-05-09","cited_by_count":9,"area":null},{"id":"2305.16483","title":"Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks","created":"2023-05-25","cited_by_count":9,"area":null},{"id":"2307.16186","title":"ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning","created":"2023-07-30","cited_by_count":9,"area":null},{"id":"2402.18002","title":"Symmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist","created":"2024-02-28","cited_by_count":9,"area":"deeprl"},{"id":"2411.04225","title":"Approximate Equivariance in Reinforcement Learning","created":"2024-11-06","cited_by_count":9,"area":"deeprl"},{"id":"2104.10105","title":"Neural Networks for Learning Counterfactual G-Invariances from Single Environments","created":"2021-04-20","cited_by_count":8,"area":null},{"id":"2209.10656","title":"Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions","created":"2022-09-21","cited_by_count":8,"area":null},{"id":"2302.10433","title":"On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis","created":"2023-02-21","cited_by_count":8,"area":null},{"id":"2507.01723","title":"SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space","created":"2025-07-02","cited_by_count":8,"area":"diffusion"},{"id":"2601.01075","title":"Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments","created":"2026-01-03","cited_by_count":8,"area":"wm"},{"id":"2306.01276","title":"Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization","created":"2023-06-02","cited_by_count":7,"area":null},{"id":"2310.17786","title":"Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates","created":"2023-10-26","cited_by_count":7,"area":null},{"id":"2405.14089","title":"Improved Canonicalization for Model Agnostic Equivariance","created":"2024-05-23","cited_by_count":7,"area":null},{"id":"2206.01233","title":"Equivariant Reinforcement Learning for Quadrotor UAV","created":"2022-06-02","cited_by_count":6,"area":null},{"id":"2206.03674","title":"Integrating Symmetry into Differentiable Planning with Steerable Convolutions","created":"2022-06-08","cited_by_count":6,"area":null},{"id":"2210.08153","title":"CUP: Critic-Guided Policy Reuse","created":"2022-10-15","cited_by_count":6,"area":null},{"id":"2307.15325","title":"Equivariance and partial observations in Koopman operator theory for partial differential equations","created":"2023-07-28","cited_by_count":6,"area":null},{"id":"2308.11842","title":"${\\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning","created":"2023-08-23","cited_by_count":6,"area":null},{"id":"2309.13043","title":"E(2)-Equivariant Graph Planning for Navigation","created":"2023-09-22","cited_by_count":6,"area":null},{"id":"2406.15753","title":"The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret","created":"2024-06-22","cited_by_count":6,"area":"alignment"},{"id":"2407.13364","title":"Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction","created":"2024-07-18","cited_by_count":6,"area":"deeprl"},{"id":"2208.13687","title":"Categorical semantics of compositional reinforcement learning","created":"2022-08-29","cited_by_count":5,"area":null},{"id":"2309.02711","title":"Addressing imperfect symmetry: A novel symmetry-learning actor-critic extension","created":"2023-09-06","cited_by_count":5,"area":null},{"id":"2406.13961","title":"Equivariant Offline Reinforcement Learning","created":"2024-06-20","cited_by_count":5,"area":"offlinerl"},{"id":"2505.05287","title":"Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation","created":"2025-05-08","cited_by_count":5,"area":"deeprl"},{"id":"2110.08092","title":"Equivariant and Invariant Reynolds Networks","created":"2021-10-15","cited_by_count":4,"area":null},{"id":"2403.12856","title":"Equivariant Ensembles and Regularization for Reinforcement Learning in Map-based Path Planning","created":"2024-03-19","cited_by_count":4,"area":"deeprl"},{"id":"2404.07373","title":"Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees","created":"2024-04-10","cited_by_count":4,"area":null},{"id":"2410.16972","title":"Sample-efficient Bayesian Optimisation Using Known Invariances","created":"2024-10-22","cited_by_count":4,"area":null},{"id":"2412.12237","title":"Equivariant Action Sampling for Reinforcement Learning and Planning","created":"2024-12-16","cited_by_count":4,"area":"deeprl"},{"id":"2104.04848","title":"Autoequivariant Network Search via Group Decomposition","created":"2021-04-10","cited_by_count":3,"area":null},{"id":"2204.00888","title":"Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Tasks","created":"2022-04-02","cited_by_count":3,"area":null},{"id":"2211.08282","title":"Homomorphic Self-Supervised Learning","created":"2022-11-15","cited_by_count":3,"area":null},{"id":"2302.04798","title":"Equivariant MuZero","created":"2023-02-09","cited_by_count":3,"area":"wm"},{"id":"2306.13872","title":"Learning from Pixels with Expert Observations","created":"2023-06-24","cited_by_count":3,"area":null},{"id":"2309.07578","title":"Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning","created":"2023-09-14","cited_by_count":3,"area":"offlinerl"},{"id":"2406.15025","title":"SiT: Symmetry-Invariant Transformers for Generalisation in Reinforcement Learning","created":"2024-06-21","cited_by_count":3,"area":"deeprl"},{"id":"2410.12983","title":"Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control","created":"2024-10-16","cited_by_count":3,"area":"deeprl"},{"id":"2505.13569","title":"Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders","created":"2025-05-19","cited_by_count":3,"area":null},{"id":"2507.20853","title":"Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces","created":"2025-07-28","cited_by_count":3,"area":"deeprl"},{"id":"2512.00915","title":"Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments","created":"2025-11-30","cited_by_count":3,"area":"deeprl"},{"id":"2102.04220","title":"Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning","created":"2021-02-08","cited_by_count":2,"area":null},{"id":"2111.10297","title":"Expert-Guided Symmetry Detection in Markov Decision Processes","created":"2021-11-19","cited_by_count":2,"area":null},{"id":"2205.01927","title":"Probabilistic Symmetry for Multi-Agent Dynamics","created":"2022-05-04","cited_by_count":2,"area":null},{"id":"2211.00086","title":"Disentangled (Un)Controllable Features","created":"2022-10-31","cited_by_count":2,"area":null},{"id":"2407.12505","title":"Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments","created":"2024-07-17","cited_by_count":2,"area":"deeprl"},{"id":"2409.11238","title":"Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems","created":"2024-09-17","cited_by_count":2,"area":"deeprl"},{"id":"2502.20500","title":"Equivariant Reinforcement Learning Frameworks for Quadrotor Low-Level Control","created":"2025-02-27","cited_by_count":2,"area":"deeprl"},{"id":"2503.15615","title":"PEnGUiN: Partially Equivariant Graph NeUral Networks for Sample Efficient MARL","created":"2025-03-19","cited_by_count":2,"area":null},{"id":"2508.01247","title":"Coordinated Humanoid Robot Locomotion with Symmetry Equivariant Reinforcement Learning Policy","created":"2025-08-02","cited_by_count":2,"area":"deeprl"},{"id":"2605.10910","title":"Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis","created":"2026-05-11","cited_by_count":2,"area":"deeprl"},{"id":"2607.16314","title":"Depth-Regularized JEPA World Models Learn More Transferable Representations from Real Outdoor Robot Data","created":"2026-07-15","cited_by_count":2,"area":"wm"},{"id":"2608.00908","title":"Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control","created":"2026-08-02","cited_by_count":2,"area":null},{"id":"2107.09301","title":"A Bayesian Approach to Invariant Deep Neural Networks","created":"2021-07-20","cited_by_count":1,"area":null},{"id":"2112.09943","title":"Data Augmentation through Expert-guided Symmetry Detection to Improve Performance in Offline Reinforcement Learning","created":"2021-12-18","cited_by_count":1,"area":"offlinerl"}],"next_cursor":"100"}