Search Results for author: Yueh-Hua Wu

Found 13 papers, 5 papers with code

DNAct: Diffusion Guided Multi-Task 3D Policy Learning

no code implementations7 Mar 2024 Ge Yan, Yueh-Hua Wu, Xiaolong Wang

To learn a generalizable multi-task policy with few demonstrations, the pre-training phase of DNAct leverages neural rendering to distill 2D semantic features from foundation models such as Stable Diffusion to a 3D space, which provides a comprehensive semantic understanding regarding the scene.

Neural Rendering

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

1 code implementation31 Aug 2023 Yanjie Ze, Ge Yan, Yueh-Hua Wu, Annabella Macaluso, Yuying Ge, Jianglong Ye, Nicklas Hansen, Li Erran Li, Xiaolong Wang

To incorporate semantics in 3D, the reconstruction module utilizes a vision-language foundation model ($\textit{e. g.}$, Stable Diffusion) to distill rich semantic information into the deep 3D voxel.

Decision Making

Elastic Decision Transformer

no code implementations NeurIPS 2023 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.

Atari Games D4RL +1

Learning Generalizable Dexterous Manipulation from Human Grasp Affordance

no code implementations5 Apr 2022 Yueh-Hua Wu, Jiashun Wang, Xiaolong Wang

In this paper, we propose to learn dexterous manipulation using large-scale demonstrations with diverse 3D objects in a category, which are generated from a human grasp affordance model.

Imitation Learning Representation Learning

DexMV: Imitation Learning for Dexterous Manipulation from Human Videos

1 code implementation12 Aug 2021 Yuzhe Qin, Yueh-Hua Wu, Shaowei Liu, Hanwen Jiang, Ruihan Yang, Yang Fu, Xiaolong Wang

While significant progress has been made on understanding hand-object interactions in computer vision, it is still very challenging for robots to perform complex dexterous manipulation.

Imitation Learning motion retargeting +1

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

no code implementations19 May 2020 Yueh-Hua Wu, I-Hau Yeh, David Hu, Hong-Yuan Mark Liao

Specifically, we are required to provide a solution that is able to (1) handle the traffic signal control when certain surveillance cameras that retrieve information for reinforcement learning are down, (2) learn from batch data without a traffic simulator, and (3) make control decisions without shared information across intersections.

Multi-agent Reinforcement Learning reinforcement-learning +1

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

124 code implementations27 Nov 2019 Chien-Yao Wang, Hong-Yuan Mark Liao, I-Hau Yeh, Yueh-Hua Wu, Ping-Yang Chen, Jun-Wei Hsieh

Neural networks have enabled state-of-the-art approaches to achieve incredible results on computer vision tasks such as object detection.

Attribute Image Classification +1

Model Imitation for Model-Based Reinforcement Learning

no code implementations25 Sep 2019 Yueh-Hua Wu, Ting-Han Fan, Peter J. Ramadge, Hao Su

Based on the claim, we propose to learn the transition model by matching the distributions of multi-step rollouts sampled from the transition model and the real ones via WGAN.

Model-based Reinforcement Learning reinforcement-learning +1

A Regulation Enforcement Solution for Multi-agent Reinforcement Learning

no code implementations29 Jan 2019 Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin

If artificially intelligent (AI) agents make decisions on behalf of human beings, we would hope they can also follow established regulations while interacting with humans or other AI agents.

Management Multi-agent Reinforcement Learning +2

ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models

no code implementations6 Sep 2018 Yueh-Hua Wu, Fan-Yun Sun, Yen-Yu Chang, Shou-De Lin

This work provides a thorough study on how reward scaling can affect performance of deep reinforcement learning agents.

reinforcement-learning Reinforcement Learning (RL)

A Memory-Network Based Solution for Multivariate Time-Series Forecasting

2 code implementations6 Sep 2018 Yen-Yu Chang, Fan-Yun Sun, Yueh-Hua Wu, Shou-De Lin

Inspired by Memory Network proposed for solving the question-answering task, we propose a deep learning based model named Memory Time-series network (MTNet) for time series forecasting.

Multivariate Time Series Forecasting Question Answering +1

A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents

1 code implementation12 Dec 2017 Yueh-Hua Wu, Shou-De Lin

This paper proposes a low-cost, easily realizable strategy to equip a reinforcement learning (RL) agent the capability of behaving ethically.

Ethics reinforcement-learning +1

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