activity
20182026
most citedCSPNet: A New Backbone that can Enhance Learning Capability of CNN

361 citations · 377 across the 4 of their papers we have counts for

collaborators

10 papers

cs.RO2026

CounterAlign: Counterfactual Supervision for Vision-Language-Action Models

Haru Kondoh, Kei Ota, Asako Kanezaki +1

Vision-Language-Action (VLA) models are typically trained with behavior cloning (BC) on expert demonstrations. However, BC provides only positive supervision for expert actions, wi…

cs.RO2023

GNFactor: Multi-Task Real Robot Learning with Generalizable Neural Feature Fields

Yanjie Ze, Ge Yan, Yueh-Hua Wu +6

It is a long-standing problem in robotics to develop agents capable of executing diverse manipulation tasks from visual observations in unstructured real-world environments. To ach…

cs.LG2023

Elastic Decision Transformer

Yueh-Hua Wu, Xiaolong Wang, Masashi Hamaya

This paper introduces Elastic Decision Transformer (EDT), a significant advancement over the existing Decision Transformer (DT) and its variants. Although DT purports to generate a…

cs.LG2020

Batch-Augmented Multi-Agent Reinforcement Learning for Efficient Traffic Signal Optimization

Yueh-Hua Wu, I-Hau Yeh, David Hu +1

The goal of this work is to provide a viable solution based on reinforcement learning for traffic signal control problems. Although the state-of-the-art reinforcement learning appr…

cs.CV2019361 cited

CSPNet: A New Backbone that can Enhance Learning Capability of CNN

Chien-Yao Wang, Hong-Yuan Mark Liao, I-Hau Yeh +3

Neural networks have enabled state-of-the-art approaches to achieve incredible results on computer vision tasks such as object detection. However, such success greatly relies on co…

cs.LG2019

Model Imitation for Model-Based Reinforcement Learning

Yueh-Hua Wu, Ting-Han Fan, Peter J. Ramadge +1

Model-based reinforcement learning (MBRL) aims to learn a dynamic model to reduce the number of interactions with real-world environments. However, due to estimation error, rollout…