b'Peilin Zhao'

research

∙ 09/20/2023

Are Large Language Models Really Robust to Word-Level Perturbations?

The swift advancement in the scale and capabilities of Large Language Mo...

0 Haoyu Wang, et al. ∙

research

∙ 08/21/2023

Differentiable Frank-Wolfe Optimization Layer

Differentiable optimization has received a significant amount of attenti...

0 Zixuan Liu, et al. ∙

research

∙ 07/30/2023

SR-R^2KAC: Improving Single Image Defocus Deblurring

We propose an efficient deep learning method for single image defocus de...

0 Peng Tang, et al. ∙

research

∙ 06/28/2023

A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges

Reaction and retrosynthesis prediction are fundamental tasks in computat...

0 Ziqiao Meng, et al. ∙

research

∙ 06/21/2023

GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection

With a long history of traditional Graph Anomaly Detection (GAD) algorit...

0 Jianheng Tang, et al. ∙

research

∙ 05/26/2023

Attention Paper: How Generative AI Reshapes Digital Shadow Industry?

The rapid development of digital economy has led to the emergence of var...

0 Qichao Wang, et al. ∙

research

∙ 05/23/2023

SyNDock: N Rigid Protein Docking via Learnable Group Synchronization

The regulation of various cellular processes heavily relies on the prote...

0 Yuanfeng Ji, et al. ∙

research

∙ 04/09/2023

Reweighted Mixup for Subpopulation Shift

Subpopulation shift exists widely in many real-world applications, which...

0 Zongbo Han, et al. ∙

research

∙ 03/23/2023

Fairness-guided Few-shot Prompting for Large Language Models

Large language models have demonstrated surprising ability to perform in...

3 Huan Ma, et al. ∙

research

∙ 03/13/2023

Deploying Offline Reinforcement Learning with Human Feedback

Reinforcement learning (RL) has shown promise for decision-making tasks ...

0 Ziniu Li, et al. ∙

research

∙ 02/24/2023

Towards Stable Test-Time Adaptation in Dynamic Wild World

Test-time adaptation (TTA) has shown to be effective at tackling distrib...

0 Shuaicheng Niu, et al. ∙

research

∙ 11/30/2022

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder

Graph neural networks (GNNs) are popular weapons for modeling relational...

0 Ziqi Gao, et al. ∙

research

∙ 10/27/2022

Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network

Binding affinity prediction of three-dimensional (3D) protein ligand com...

0 Yiqiang Yi, et al. ∙

research

∙ 10/20/2022

Vertical Federated Linear Contextual Bandits

In this paper, we investigate a novel problem of building contextual ban...

0 Zeyu Cao, et al. ∙

research

∙ 10/19/2022

Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation

A promising paradigm for offline reinforcement learning (RL) is to const...

0 Chengqian Gao, et al. ∙

research

∙ 10/14/2022

Pareto-aware Neural Architecture Generation for Diverse Computational Budgets

Designing feasible and effective architectures under diverse computation...

0 Yong Guo, et al. ∙

research

∙ 09/30/2022

Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree

Retrosynthetic planning plays a critical role in drug discovery and orga...

10 Songtao Liu, et al. ∙

research

∙ 09/27/2022

MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction

Retrosynthesis is a major task for drug discovery. It is formulated as a...

0 Jiahan Liu, et al. ∙

research

∙ 09/19/2022

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

Subpopulation shift wildly exists in many real-world machine learning ap...

0 Zongbo Han, et al. ∙

research

∙ 09/16/2022

ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery

The last decade has witnessed a prosperous development of computational ...

0 Lanqing Li, et al. ∙

research

∙ 08/11/2022

Quantized Adaptive Subgradient Algorithms and Their Applications

Data explosion and an increase in model size drive the remarkable advanc...

10 Ke Xu, et al. ∙

research

∙ 05/23/2022

ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification

Graph contrastive learning (GCL) has attracted a surge of attention due ...

0 Liang Zeng, et al. ∙

research

∙ 05/20/2022

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection

Deep graph learning has achieved remarkable progresses in both business ...

0 Bingzhe Wu, et al. ∙

research

∙ 05/16/2022

Multi-scale Attention Flow for Probabilistic Time Series Forecasting

The probability prediction of multivariate time series is a notoriously ...

0 Shibo Feng, et al. ∙

research

∙ 05/12/2022

GPN: A Joint Structural Learning Framework for Graph Neural Networks

Graph neural networks (GNNs) have been applied into a variety of graph t...

0 Qianggang Ding, et al. ∙

research

∙ 04/16/2022

DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup

Recently, federated learning has emerged as a promising approach for tra...

0 Bingzhe Wu, et al. ∙

research

∙ 04/06/2022

Efficient Test-Time Model Adaptation without Forgetting

Test-time adaptation (TTA) seeks to tackle potential distribution shifts...

1 Shuaicheng Niu, et al. ∙

research

∙ 03/03/2022

Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference

Learning set functions becomes increasingly more important in many appli...

0 Zijing Ou, et al. ∙

research

∙ 02/17/2022

Transformer for Graphs: An Overview from Architecture Perspective

Recently, Transformer model, which has achieved great success in many ar...

0 Erxue Min, et al. ∙

research

∙ 01/25/2022

Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction

Click-Through Rate (CTR) prediction, is an essential component of online...

0 Erxue Min, et al. ∙

research

∙ 01/24/2022

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery – A Focus on Affinity Prediction Problems with Noise Annotations

AI-aided drug discovery (AIDD) is gaining increasing popularity due to i...

1 Yuanfeng Ji, et al. ∙

research

∙ 12/20/2021

RetroComposer: Discovering Novel Reactions by Composing Templates for Retrosynthesis Prediction

The main target of retrosynthesis is to recursively decompose desired mo...

0 Chaochao Yan, et al. ∙

research

∙ 12/13/2021

SVIP: Sequence VerIfication for Procedures in Videos

In this paper, we propose a novel sequence verification task that aims t...

0 Yicheng Qian, et al. ∙

research

∙ 12/01/2021

Graph Convolutional Module for Temporal Action Localization in Videos

Temporal action localization has long been researched in computer vision...

0 Runhao Zeng, et al. ∙

research

∙ 11/14/2021

p-Laplacian Based Graph Neural Networks

Graph neural networks (GNNs) have demonstrated superior performance for ...

0 Guoji Fu, et al. ∙

research

∙ 10/26/2021

Meta-learning with an Adaptive Task Scheduler

To benefit the learning of a new task, meta-learning has been proposed t...

11 Huaxiu Yao, et al. ∙

research

∙ 10/15/2021

Value Penalized Q-Learning for Recommender Systems

Scaling reinforcement learning (RL) to recommender systems (RS) is promi...

0 Chengqian Gao, et al. ∙

research

∙ 09/08/2021

Local Augmentation for Graph Neural Networks

Data augmentation has been widely used in image data and linguistic data...

1 Songtao Liu, et al. ∙

research

∙ 07/01/2021

AdaXpert: Adapting Neural Architecture for Growing Data

In real-world applications, data often come in a growing manner, where t...

0 Shuaicheng Niu, et al. ∙

research

∙ 05/29/2021

Learning Graphon Autoencoders for Generative Graph Modeling

Graphon is a nonparametric model that generates graphs with arbitrary si...

0 Hongteng Xu, et al. ∙

research

∙ 05/23/2021

Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation

Recent studies imply that deep neural networks are vulnerable to adversa...

0 Jinyu Yang, et al. ∙

research

∙ 04/15/2021

Sparse online relative similarity learning

For many data mining and machine learning tasks, the quality of a simila...

20 Dezhong Yao, et al. ∙

research

∙ 04/14/2021

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

Graph Neural Network (GNN) research is rapidly growing thanks to the cap...

54 Chaoyang He, et al. ∙

research

∙ 02/27/2021

Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets

Designing feasible and effective architectures under diverse computation...

0 Yong Guo, et al. ∙

research

∙ 02/20/2021

Towards Accurate and Compact Architectures via Neural Architecture Transformer

Designing effective architectures is one of the key factors behind the s...

0 Yong Guo, et al. ∙

research

∙ 12/16/2020

Hierarchical Graph Capsule Network

Graph Neural Networks (GNNs) draw their strength from explicitly modelin...

0 Jinyu Yang, et al. ∙

research

∙ 11/25/2020

Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings

We present JueWu-SL, the first supervised-learning-based artificial inte...

6 Deheng Ye, et al. ∙

research

∙ 11/04/2020

RetroXpert: Decompose Retrosynthesis Prediction like a Chemist

Retrosynthesis is the process of recursively decomposing target molecule...

7 Chaochao Yan, et al. ∙

research

∙ 07/12/2020

Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?

Graph Identification (GI) has long been researched in graph learning and...

0 Tian Bian, et al. ∙

research

∙ 04/30/2020

COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19

The outbreak of novel coronavirus disease 2019 (COVID-19) has already in...

9 Yifan Zhang, et al. ∙

Peilin Zhao

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