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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...
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08/21/2023
Differentiable Frank-Wolfe Optimization Layer
Differentiable optimization has received a significant amount of attenti...
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07/30/2023
SR-R^2KAC: Improving Single Image Defocus Deblurring
We propose an efficient deep learning method for single image defocus de...
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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...
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06/21/2023
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
With a long history of traditional Graph Anomaly Detection (GAD) algorit...
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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...
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05/23/2023
SyNDock: N Rigid Protein Docking via Learnable Group Synchronization
The regulation of various cellular processes heavily relies on the prote...
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04/09/2023
Reweighted Mixup for Subpopulation Shift
Subpopulation shift exists widely in many real-world applications, which...
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03/23/2023
Fairness-guided Few-shot Prompting for Large Language Models
Large language models have demonstrated surprising ability to perform in...
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03/13/2023
Deploying Offline Reinforcement Learning with Human Feedback
Reinforcement learning (RL) has shown promise for decision-making tasks ...
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02/24/2023
Towards Stable Test-Time Adaptation in Dynamic Wild World
Test-time adaptation (TTA) has shown to be effective at tackling distrib...
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11/30/2022
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
Graph neural networks (GNNs) are popular weapons for modeling relational...
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10/27/2022
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network
Binding affinity prediction of three-dimensional (3D) protein ligand com...
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10/20/2022
Vertical Federated Linear Contextual Bandits
In this paper, we investigate a novel problem of building contextual ban...
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10/19/2022
Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation
A promising paradigm for offline reinforcement learning (RL) is to const...
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10/14/2022
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
Designing feasible and effective architectures under diverse computation...
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09/30/2022
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree
Retrosynthetic planning plays a critical role in drug discovery and orga...
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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...
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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...
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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 ...
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08/11/2022
Quantized Adaptive Subgradient Algorithms and Their Applications
Data explosion and an increase in model size drive the remarkable advanc...
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05/23/2022
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification
Graph contrastive learning (GCL) has attracted a surge of attention due ...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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05/16/2022
Multi-scale Attention Flow for Probabilistic Time Series Forecasting
The probability prediction of multivariate time series is a notoriously ...
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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...
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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...
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04/06/2022
Efficient Test-Time Model Adaptation without Forgetting
Test-time adaptation (TTA) seeks to tackle potential distribution shifts...
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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...
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02/17/2022
Transformer for Graphs: An Overview from Architecture Perspective
Recently, Transformer model, which has achieved great success in many ar...
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01/25/2022
Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction
Click-Through Rate (CTR) prediction, is an essential component of online...
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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...
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12/20/2021
RetroComposer: Discovering Novel Reactions by Composing Templates for Retrosynthesis Prediction
The main target of retrosynthesis is to recursively decompose desired mo...
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12/13/2021
SVIP: Sequence VerIfication for Procedures in Videos
In this paper, we propose a novel sequence verification task that aims t...
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12/01/2021
Graph Convolutional Module for Temporal Action Localization in Videos
Temporal action localization has long been researched in computer vision...
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11/14/2021
p-Laplacian Based Graph Neural Networks
Graph neural networks (GNNs) have demonstrated superior performance for ...
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10/26/2021
Meta-learning with an Adaptive Task Scheduler
To benefit the learning of a new task, meta-learning has been proposed t...
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10/15/2021
Value Penalized Q-Learning for Recommender Systems
Scaling reinforcement learning (RL) to recommender systems (RS) is promi...
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09/08/2021
Local Augmentation for Graph Neural Networks
Data augmentation has been widely used in image data and linguistic data...
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07/01/2021
AdaXpert: Adapting Neural Architecture for Growing Data
In real-world applications, data often come in a growing manner, where t...
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05/29/2021
Learning Graphon Autoencoders for Generative Graph Modeling
Graphon is a nonparametric model that generates graphs with arbitrary si...
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05/23/2021
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Recent studies imply that deep neural networks are vulnerable to adversa...
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04/15/2021
Sparse online relative similarity learning
For many data mining and machine learning tasks, the quality of a simila...
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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...
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02/27/2021
Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets
Designing feasible and effective architectures under diverse computation...
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02/20/2021
Towards Accurate and Compact Architectures via Neural Architecture Transformer
Designing effective architectures is one of the key factors behind the s...
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12/16/2020
Hierarchical Graph Capsule Network
Graph Neural Networks (GNNs) draw their strength from explicitly modelin...
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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...
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11/04/2020
RetroXpert: Decompose Retrosynthesis Prediction like a Chemist
Retrosynthesis is the process of recursively decomposing target molecule...
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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...
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04/30/2020
