Drifting Field Policy: A One-Step Generative Policy via Wasserstein Gradient Flow
Fuente:
arXiv
Guardado en:
| Autores principales: | Koo, Juil, Park, Mingue, Choi, Jiwon, Min, Yunhong, Sung, Minhyuk |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
BézierFlow: Learning Bézier Stochastic Interpolant Schedulers for Few-Step Generation
por: Min, Yunhong, et al.
Publicado: (2025)
por: Min, Yunhong, et al.
Publicado: (2025)
DiffusionRollout: Uncertainty-Aware Rollout Planning in Long-Horizon PDE Solving
por: Yoo, Seungwoo, et al.
Publicado: (2026)
por: Yoo, Seungwoo, et al.
Publicado: (2026)
Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients?
por: Onoda, Ku, et al.
Publicado: (2026)
por: Onoda, Ku, et al.
Publicado: (2026)
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions
por: Jain, Ayush, et al.
Publicado: (2024)
por: Jain, Ayush, et al.
Publicado: (2024)
Online Continual Learning For Interactive Instruction Following Agents
por: Kim, Byeonghwi, et al.
Publicado: (2024)
por: Kim, Byeonghwi, et al.
Publicado: (2024)
Implicit Drifting Policy: One-Step Action Generation via Conditional Expert Geometry
por: Yang, Zemin, et al.
Publicado: (2026)
por: Yang, Zemin, et al.
Publicado: (2026)
Mollification Effects of Policy Gradient Methods
por: Wang, Tao, et al.
Publicado: (2024)
por: Wang, Tao, et al.
Publicado: (2024)
PairFlow: Closed-Form Source-Target Coupling for Few-Step Generation in Discrete Flow Models
por: Park, Mingue, et al.
Publicado: (2025)
por: Park, Mingue, et al.
Publicado: (2025)
Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning
por: Shitanda, Naoki, et al.
Publicado: (2026)
por: Shitanda, Naoki, et al.
Publicado: (2026)
Gradient Flow Drifting: Generative Modeling via Wasserstein Gradient Flows of KDE-Approximated Divergences
por: Cao, Jiarui, et al.
Publicado: (2026)
por: Cao, Jiarui, et al.
Publicado: (2026)
Foundation Policies with Hilbert Representations
por: Park, Seohong, et al.
Publicado: (2024)
por: Park, Seohong, et al.
Publicado: (2024)
On the Wasserstein Gradient Flow Interpretation of Drifting Models
por: Gretton, Arthur, et al.
Publicado: (2026)
por: Gretton, Arthur, et al.
Publicado: (2026)
FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning
por: Alles, Marvin, et al.
Publicado: (2025)
por: Alles, Marvin, et al.
Publicado: (2025)
Real-Time Execution of Action Chunking Flow Policies
por: Black, Kevin, et al.
Publicado: (2025)
por: Black, Kevin, et al.
Publicado: (2025)
One-Step Flow Policy: Self-Distillation for Fast Visuomotor Policies
por: Li, Shaolong, et al.
Publicado: (2026)
por: Li, Shaolong, et al.
Publicado: (2026)
A Multi-Fidelity Control Variate Approach for Policy Gradient Estimation
por: Liu, Xinjie, et al.
Publicado: (2025)
por: Liu, Xinjie, et al.
Publicado: (2025)
Imagination Policy: Using Generative Point Cloud Models for Learning Manipulation Policies
por: Huang, Haojie, et al.
Publicado: (2024)
por: Huang, Haojie, et al.
Publicado: (2024)
Latent Policy Steering through One-Step Flow Policies
por: Im, Hokyun, et al.
Publicado: (2026)
por: Im, Hokyun, et al.
Publicado: (2026)
WarmPrior: Straightening Flow-Matching Policies with Temporal Priors
por: Kang, Sinjae, et al.
Publicado: (2026)
por: Kang, Sinjae, et al.
Publicado: (2026)
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms
por: Schoepp, Sheila, et al.
Publicado: (2024)
por: Schoepp, Sheila, et al.
Publicado: (2024)
Flow Matching Policy Gradients
por: McAllister, David, et al.
Publicado: (2025)
por: McAllister, David, et al.
Publicado: (2025)
Safe Exploration via Policy Priors
por: Wendl, Manuel, et al.
Publicado: (2026)
por: Wendl, Manuel, et al.
Publicado: (2026)
GenORM: Generalizable One-shot Rope Manipulation with Parameter-Aware Policy
por: Kuroki, So, et al.
Publicado: (2023)
por: Kuroki, So, et al.
Publicado: (2023)
DISC: Decoupling Instruction from State-Conditioned Control via Policy Generation
por: Ren, Hanxiang, et al.
Publicado: (2026)
por: Ren, Hanxiang, et al.
Publicado: (2026)
A Review of Online Diffusion Policy RL Algorithms for Scalable Robotic Control
por: Choi, Wonhyeok, et al.
Publicado: (2026)
por: Choi, Wonhyeok, et al.
Publicado: (2026)
IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation
por: Rana, Krishan, et al.
Publicado: (2025)
por: Rana, Krishan, et al.
Publicado: (2025)
Discrete Variational Autoencoding via Policy Search
por: Drolet, Michael, et al.
Publicado: (2025)
por: Drolet, Michael, et al.
Publicado: (2025)
Distilling Reinforcement Learning Policies for Interpretable Robot Locomotion: Gradient Boosting Machines and Symbolic Regression
por: Acero, Fernando, et al.
Publicado: (2024)
por: Acero, Fernando, et al.
Publicado: (2024)
Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation
por: Nakanishi, Kosuke, et al.
Publicado: (2025)
por: Nakanishi, Kosuke, et al.
Publicado: (2025)
Grasp Anything: Combining Teacher-Augmented Policy Gradient Learning with Instance Segmentation to Grasp Arbitrary Objects
por: Mosbach, Malte, et al.
Publicado: (2024)
por: Mosbach, Malte, et al.
Publicado: (2024)
Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Coordination by Multi-Critic Policy Gradient Optimization
por: Alon, Yoav, et al.
Publicado: (2020)
por: Alon, Yoav, et al.
Publicado: (2020)
LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models
por: Peng, Zengqi, et al.
Publicado: (2025)
por: Peng, Zengqi, et al.
Publicado: (2025)
Robust Policy Learning via Offline Skill Diffusion
por: Kim, Woo Kyung, et al.
Publicado: (2024)
por: Kim, Woo Kyung, et al.
Publicado: (2024)
Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model
por: Yuan, Xiu, et al.
Publicado: (2024)
por: Yuan, Xiu, et al.
Publicado: (2024)
Data Augmentation for Instruction Following Policies via Trajectory Segmentation
por: Höpner, Niklas, et al.
Publicado: (2025)
por: Höpner, Niklas, et al.
Publicado: (2025)
In-Context Policy Adaptation via Cross-Domain Skill Diffusion
por: Yoo, Minjong, et al.
Publicado: (2025)
por: Yoo, Minjong, et al.
Publicado: (2025)
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
por: Xu, Charles, et al.
Publicado: (2024)
por: Xu, Charles, et al.
Publicado: (2024)
Multi-Modal Manipulation via Multi-Modal Policy Consensus
por: Chen, Haonan, et al.
Publicado: (2025)
por: Chen, Haonan, et al.
Publicado: (2025)
Psi-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models
por: Yoon, Taehoon, et al.
Publicado: (2025)
por: Yoon, Taehoon, et al.
Publicado: (2025)
Evolutionary Policy Optimization
por: Wang, Jianren, et al.
Publicado: (2025)
por: Wang, Jianren, et al.
Publicado: (2025)
Ejemplares similares
-
BézierFlow: Learning Bézier Stochastic Interpolant Schedulers for Few-Step Generation
por: Min, Yunhong, et al.
Publicado: (2025) -
DiffusionRollout: Uncertainty-Aware Rollout Planning in Long-Horizon PDE Solving
por: Yoo, Seungwoo, et al.
Publicado: (2026) -
Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients?
por: Onoda, Ku, et al.
Publicado: (2026) -
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions
por: Jain, Ayush, et al.
Publicado: (2024) -
Online Continual Learning For Interactive Instruction Following Agents
por: Kim, Byeonghwi, et al.
Publicado: (2024)