Copertina

Quantile-Coupled Flow Matching for Distributional Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Groom, Michael, Darvariu, Victor-Alexandru, Kunze, Lars, Wilson, James, Hawes, Nick
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Robotics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Risk-Aware Reinforcement Learning for Mobile Manipulation
di: Groom, Michael, et al.
Pubblicazione: (2026)

JaxWildfire: A GPU-Accelerated Wildfire Simulator for Reinforcement Learning
di: Çakır, Ufuk, et al.
Pubblicazione: (2025)

Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
di: Schutz, Alex, et al.
Pubblicazione: (2025)

On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows
di: Tee, Jia Yu, et al.
Pubblicazione: (2023)

A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers
di: Omeiza, Daniel, et al.
Pubblicazione: (2024)

Graph Reinforcement Learning for Combinatorial Optimization: A Survey and Unifying Perspective
di: Darvariu, Victor-Alexandru, et al.
Pubblicazione: (2024)

Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery
di: Darvariu, Victor-Alexandru, et al.
Pubblicazione: (2023)

ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning
di: Zhang, Tonghe, et al.
Pubblicazione: (2025)

Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies
di: Pisacane, Alexei, et al.
Pubblicazione: (2024)

Graph Neural Modeling of Network Flows
di: Darvariu, Victor-Alexandru, et al.
Pubblicazione: (2022)

GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation
di: Panagiotaki, Efimia, et al.
Pubblicazione: (2024)

Safety-Aware Reinforcement Learning for Control via Risk-Sensitive Action-Value Iteration and Quantile Regression
di: Enwerem, Clinton, et al.
Pubblicazione: (2025)

Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models
di: Lyu, Mingyang, et al.
Pubblicazione: (2025)

No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
di: Rutherford, Alexander, et al.
Pubblicazione: (2024)

Riemannian Flow Matching Policy for Robot Motion Learning
di: Braun, Max, et al.
Pubblicazione: (2024)

Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
di: Liu, Guangyi, et al.
Pubblicazione: (2025)

Trust-based Consensus in Multi-Agent Reinforcement Learning Systems
di: Fung, Ho Long, et al.
Pubblicazione: (2022)

Generating Causal Explanations of Vehicular Agent Behavioural Interactions with Learnt Reward Profiles
di: Howard, Rhys, et al.
Pubblicazione: (2025)

Flow Matching Policy Gradients
di: McAllister, David, et al.
Pubblicazione: (2025)

PolicyFlow: Policy Optimization with Continuous Normalizing Flow in Reinforcement Learning
di: Yang, Shunpeng, et al.
Pubblicazione: (2026)

High-Performance Reinforcement Learning on Spot: Optimizing Simulation Parameters with Distributional Measures
di: Miller, AJ, et al.
Pubblicazione: (2025)

Estimator-Coupled Reinforcement Learning for Robust Purely Tactile In-Hand Manipulation
di: Röstel, Lennart, et al.
Pubblicazione: (2023)

Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap
di: Tekkesinoglu, Sule, et al.
Pubblicazione: (2024)

Large Language Models are Effective Priors for Causal Graph Discovery
di: Darvariu, Victor-Alexandru, et al.
Pubblicazione: (2024)

Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data
di: Li, Tianyu, et al.
Pubblicazione: (2025)

Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning
di: Schneider, Lukas, et al.
Pubblicazione: (2023)

LUMOS: Language-Conditioned Imitation Learning with World Models
di: Nematollahi, Iman, et al.
Pubblicazione: (2025)

Dynamic Objects Relocalization in Changing Environments with Flow Matching
di: Argenziano, Francesco, et al.
Pubblicazione: (2025)

Fast and Robust Visuomotor Riemannian Flow Matching Policy
di: Ding, Haoran, et al.
Pubblicazione: (2024)

Score and Distribution Matching Policy: Advanced Accelerated Visuomotor Policies via Matched Distillation
di: Jia, Bofang, et al.
Pubblicazione: (2024)

SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
di: Zhang, Yixian, et al.
Pubblicazione: (2025)

NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
di: Panagiotaki, Efimia, et al.
Pubblicazione: (2024)

Flow-Opt: Scalable Centralized Multi-Robot Trajectory Optimization with Flow Matching and Differentiable Optimization
di: Idoko, Simon, et al.
Pubblicazione: (2025)

ArrayBot: Reinforcement Learning for Generalizable Distributed Manipulation through Touch
di: Xue, Zhengrong, et al.
Pubblicazione: (2023)

Flow Matching Ergodic Coverage
di: Sun, Max Muchen, et al.
Pubblicazione: (2025)

STRIDE: Structured Lagrangian and Stochastic Residual Dynamics via Flow Matching
di: Kotecha, Prakrut, et al.
Pubblicazione: (2026)

VFP: Variational Flow-Matching Policy for Multi-Modal Robot Manipulation
di: Zhai, Xuanran, et al.
Pubblicazione: (2025)

Accelerating Atomic Fine Structure Determination with Graph Reinforcement Learning
di: Ding, M., et al.
Pubblicazione: (2025)

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning
di: Alles, Marvin, et al.
Pubblicazione: (2025)

Sampling for Model Predictive Trajectory Planning in Autonomous Driving using Normalizing Flows
di: Rabenstein, Georg, et al.
Pubblicazione: (2024)