b'Jian Peng'

research

∙ 09/12/2023

InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Diffusion models have revolutionized text-to-image generation with its e...

0 Xingchao Liu, et al. ∙

research

∙ 03/06/2023

3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction

Rich data and powerful machine learning models allow us to design drugs ...

0 Jiaqi Guan, et al. ∙

research

∙ 11/20/2022

Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation

Learning new task-specific skills from a few trials is a fundamental cha...

0 Zhizhou Ren, et al. ∙

research

∙ 07/12/2022

Split Time Series into Patches: Rethinking Long-term Series Forecasting with Dateformer

Time is one of the most significant characteristics of time-series, yet ...

0 Julong Young, et al. ∙

research

∙ 06/10/2022

Is Self-Supervised Learning More Robust Than Supervised Learning?

Self-supervised contrastive learning is a powerful tool to learn visual ...

8 Yuanyi Zhong, et al. ∙

research

∙ 05/15/2022

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

Deep generative models have achieved tremendous success in designing nov...

44 Xingang Peng, et al. ∙

research

∙ 04/25/2022

Imitation Learning from Observations under Transition Model Disparity

Learning to perform tasks by leveraging a dataset of expert observations...

1 Tanmay Gangwani, et al. ∙

research

∙ 03/28/2022

Equivariant Point Cloud Analysis via Learning Orientations for Message Passing

Equivariance has been a long-standing concern in various fields ranging ...

8 Shitong Luo, et al. ∙

research

∙ 03/20/2022

A 3D Molecule Generative Model for Structure-Based Drug Design

We study a fundamental problem in structure-based drug design – generati...

11 Shitong Luo, et al. ∙

research

∙ 03/02/2022

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

Protein structure prediction is an important method for understanding ge...

0 Shenggan Cheng, et al. ∙

research

∙ 01/28/2022

Directed Weight Neural Networks for Protein Structure Representation Learning

A protein performs biological functions by folding to a particular 3D st...

12 Jiahan Li, et al. ∙

research

∙ 12/04/2021

Overcome Anterograde Forgetting with Cycled Memory Networks

Learning from a sequence of tasks for a lifetime is essential for an age...

0 Jian Peng, et al. ∙

research

∙ 11/26/2021

Learning Long-Term Reward Redistribution via Randomized Return Decomposition

Many practical applications of reinforcement learning require agents to ...

6 Zhizhou Ren, et al. ∙

research

∙ 11/23/2021

Reviewing continual learning from the perspective of human-level intelligence

Humans' continual learning (CL) ability is closely related to Stability ...

2 Yifan Chang, et al. ∙

research

∙ 11/21/2021

Learning by Active Forgetting for Neural Networks

Remembering and forgetting mechanisms are two sides of the same coin in ...

7 Jian Peng, et al. ∙

research

∙ 09/18/2021

Hindsight Foresight Relabeling for Meta-Reinforcement Learning

Meta-reinforcement learning (meta-RL) algorithms allow for agents to lea...

0 Michael Wan, et al. ∙

research

∙ 08/20/2021

Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation

We present a novel semi-supervised semantic segmentation method which jo...

0 Yuanyi Zhong, et al. ∙

research

∙ 07/11/2021

Coordinate-wise Control Variates for Deep Policy Gradients

The control variates (CV) method is widely used in policy gradient estim...

3 Yuanyi Zhong, et al. ∙

research

∙ 06/22/2021

Off-Policy Reinforcement Learning with Delayed Rewards

We study deep reinforcement learning (RL) algorithms with delayed reward...

4 Beining Han, et al. ∙

research

∙ 03/30/2021

DAP: Detection-Aware Pre-training with Weak Supervision

This paper presents a detection-aware pre-training (DAP) approach, which...

0 Yuanyi Zhong, et al. ∙

research

∙ 02/20/2021

Learning Neural Generative Dynamics for Molecular Conformation Generation

We study how to generate molecule conformations (i.e., 3D structures) fr...

2 Minkai Xu, et al. ∙

research

∙ 11/05/2020

Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity

Quality-Diversity (QD) is a concept from Neuroevolution with some intrig...

2 Tanmay Gangwani, et al. ∙

research

∙ 10/29/2020

Off-Policy Interval Estimation with Lipschitz Value Iteration

Off-policy evaluation provides an essential tool for evaluating the effe...

8 Ziyang Tang, et al. ∙

research

∙ 10/23/2020

Learning Guidance Rewards with Trajectory-space Smoothing

Long-term temporal credit assignment is an important challenge in deep r...

7 Tanmay Gangwani, et al. ∙

research

∙ 09/13/2020

Efficient Competitive Self-Play Policy Optimization

Reinforcement learning from self-play has recently reported many success...

11 Yuanyi Zhong, et al. ∙

research

∙ 08/28/2020

Pre-training of Graph Neural Network for Modeling Effects of Mutations on Protein-Protein Binding Affinity

Modeling the effects of mutations on the binding affinity plays a crucia...

0 Xianggen Liu, et al. ∙

research

∙ 07/15/2020

Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer

In this paper, we propose an effective knowledge transfer framework to b...

2 Yuanyi Zhong, et al. ∙

research

∙ 07/04/2020

Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion

Langevin diffusion is a powerful method for nonconvex optimization, whic...

0 Yi Chen, et al. ∙

research

∙ 06/12/2020

Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch

Deep reinforcement learning (RL) algorithms have achieved great success ...

1 Michael Wan, et al. ∙

research

∙ 03/07/2020

DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images

Change detection is a basic task of remote sensing image processing. The...

16 Jie Chen, et al. ∙

research

∙ 03/01/2020

Stein Variational Inference for Discrete Distributions

Gradient-based approximate inference methods, such as Stein variational ...

15 Jun Han, et al. ∙

research

∙ 02/27/2020

State-only Imitation with Transition Dynamics Mismatch

Imitation Learning (IL) is a popular paradigm for training agents to ach...

10 Tanmay Gangwani, et al. ∙

research

∙ 02/21/2020

Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning

In many vision-based reinforcement learning (RL) problems, the agent con...

8 Yuanyi Zhong, et al. ∙

research

∙ 01/27/2020

Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification

Remote sensing image scene classification is a fundamental but challengi...

7 Jie Chen, et al. ∙

research

∙ 11/09/2019

DeepMask: an algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network

Detecting and masking cloud and cloud shadow from satellite remote sensi...

18 Ke Xu, et al. ∙

research

∙ 09/07/2019

HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding

Heterogeneous information network (HIN) embedding has gained increasing ...

3 Yu He, et al. ∙

research

∙ 09/05/2019

√(n)-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank

In this paper, we consider the problem of online learning of Markov deci...

4 Kefan Dong, et al. ∙

research

∙ 07/21/2019

Characterizing Attacks on Deep Reinforcement Learning

Deep reinforcement learning (DRL) has achieved great success in various ...

4 Chaowei Xiao, et al. ∙

research

∙ 06/22/2019

Learning Belief Representations for Imitation Learning in POMDPs

We consider the problem of imitation learning from expert demonstrations...

3 Tanmay Gangwani, et al. ∙

research

∙ 06/10/2019

Exploration via Hindsight Goal Generation

Goal-oriented reinforcement learning has recently been a practical frame...

6 Zhizhou Ren, et al. ∙

research

∙ 06/08/2019

A gradual, semi-discrete approach to generative network training via explicit wasserstein minimization

This paper provides a simple procedure to fit generative networks to tar...

1 Yucheng Chen, et al. ∙

research

∙ 05/31/2019

Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning

Recent advances in deep reinforcement learning algorithms have shown gre...

8 Yang Liu, et al. ∙

research

∙ 05/27/2019

Thresholding Bandit with Optimal Aggregate Regret

We consider the thresholding bandit problem, whose goal is to find arms ...

5 Chao Tao, et al. ∙

research

∙ 05/20/2019

Stochastic Variance Reduction for Deep Q-learning

Recent advances in deep reinforcement learning have achieved human-level...

5 Wei-Ye Zhao, et al. ∙

research

∙ 04/11/2019

Knowledge Flow: Improve Upon Your Teachers

A zoo of deep nets is available these days for almost any given task, an...

18 Iou-Jen Liu, et al. ∙

research

∙ 12/04/2018

Overcoming Catastrophic Forgetting by Soft Parameter Pruning

Catastrophic forgetting is a challenge issue in continual learning when ...

0 Jian Peng, et al. ∙

research

∙ 12/02/2018

Anchor Box Optimization for Object Detection

In this paper, we propose a general approach to optimize anchor boxes fo...

0 Yuanyi Zhong, et al. ∙

research

∙ 11/27/2018

Understanding the Importance of Single Directions via Representative Substitution

Understanding the internal representations of deep neural networks (DNNs...

8 Li Chen, et al. ∙

research

∙ 09/03/2018

emrQA: A Large Corpus for Question Answering on Electronic Medical Records

We propose a novel methodology to generate domain-specific large-scale q...

0 Anusri Pampari, et al. ∙

research

∙ 08/01/2018

Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy

When learning from a batch of logged bandit feedback, the discrepancy be...

0 Yuan Xie, et al. ∙

Jian Peng

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