Shuicheng Yan

发表

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

Min Lin, Zhongwen Xu, Viktor Makoviychuk, 2022, NeurIPS.

Efficient Offline Policy Optimization with a Learned Model

Zhongwen Xu, Zi-Yan Liu, Shuicheng Yan, 2022, ArXiv.

RPM: Generalizable Behaviors for Multi-Agent Reinforcement Learning

Zhongwen Xu, Bo An, Wei Qiu, 2022, ArXiv.

Mutual Information Regularized Offline Reinforcement Learning

Min Lin, Zhongwen Xu, Bingyi Kang, 2022, NeurIPS.

Spikformer: When Spiking Neural Network Meets Transformer

Yaowei Wang, Yonghong Tian, Liuliang Yuan, 2022, ArXiv.

Win: Weight-Decay-Integrated Nesterov Acceleration for Adaptive Gradient Algorithms

Pan Zhou, Xingyu Xie, Shuicheng Yan, 2022 .

Spikformer: When Spiking Neural Network Meets Transformer

Yaowei Wang, Yue-sheng Zhu, Yonghong Tian, 2022, ICLR.

SDMuse: Stochastic Differential Music Editing and Generation via Hybrid Representation

Kecheng Zhang, Chen Zhang, Shuicheng Yan, 2022, 2211.00222.

MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation Segmentation

Yefeng Zheng, Donghuan Lu, Yujia Xie, 2023, ArXiv.

D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory

Min Lin, G. Vignale, A. Neto, 2023, ICLR.

Does Federated Learning Really Need Backpropagation?

Min Lin, Chao Du, Wei Chen, 2023, ArXiv.

SDMuse: Stochastic Differential Music Editing and Generation via Hybrid Representation

Kecheng Zhang, Chen Zhang, Shuicheng Yan, 2022, IEEE Transactions on Multimedia.

CoSDA: Continual Source-Free Domain Adaptation

Chao Du, Wei Chen, Tianyu Pang, 2023, ArXiv.

Better Diffusion Models Further Improve Adversarial Training

Min Lin, Chao Du, Tianyu Pang, 2023, ArXiv.

Exploring Incompatible Knowledge Transfer in Few-shot Image Generation

Min Lin, Chao Du, Tianyu Pang, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Better Diffusion Models Further Improve Adversarial Training

Min Lin, Chao Du, Tianyu Pang, 2023, ICML.

Bag of Tricks for Training Data Extraction from Language Models

Min Lin, Yan Huang, Chao Du, 2023, ICML.

Efficient Diffusion Policies for Offline Reinforcement Learning

Chao Du, Tianyu Pang, Bingyi Kang, 2023, arXiv.org.

On Calibrating Diffusion Probabilistic Models

Min Lin, Chao Du, Tianyu Pang, 2023, NeurIPS.

Generative Table Pre-training Empowers Models for Tabular Prediction

Qian Liu, Jian Li, Shaowen Wang, 2023, EMNLP.

Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows

Min Lin, Chao Du, Tianyu Pang, 2023, arXiv.org.

Offline Prioritized Experience Replay

S. Song, Bingyi Kang, Gao Huang, 2023, ArXiv.

Learning to Optimize for Reinforcement Learning

Zhongwen Xu, Qingfeng Lan, Rupam Mahmood, 2023, arXiv.org.

Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments

Jiashi Feng, Kaixin Wang, Shuicheng Yan, 2023, ICLR.

SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning

Wei Tsang Ooi, Qizhe Xie, Tat-Seng Chua, 2023, ArXiv.

Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows

Min Lin, Chao Du, Tianyu Pang, 2023, ICML.

MULTI-AGENT REINFORCEMENT LEARNING

Zhongwen Xu, Bo An, Wei Qiu, 2023 .

Reinforcement Learning from Diverse Human Preferences

Zhongwen Xu, Bo An, Wanqi Xue, 2023, ArXiv.

Gaussian Mixture Solvers for Diffusion Models

Chao Du, Tianyu Pang, Fan Bao, 2023, ArXiv.

Efficient Diffusion Policies for Offline Reinforcement Learning

Chao Du, Tianyu Pang, Bingyi Kang, 2023, ArXiv.

MULTI-AGENT REINFORCEMENT LEARNING

Zhongwen Xu, Bo An, Wei Qiu, 2023 .

Sharing Residual Units Through Collective Tensor Factorization in Deep Neural Networks

Chen Yunpeng, Jin Xiaojie, Kang Bingyi, 2017, ArXiv.

Improving and Benchmarking Offline Reinforcement Learning Algorithms

Bingyi Kang, Yang Yue, Xiao Ma, 2023, ArXiv.

Visual Imitation Learning with Patch Rewards

Zhongwen Xu, Minghuan Liu, Weinan Zhang, 2023, ICLR.