2024
Point Cloud Completion via Relative Point Position Encoding and Regional Attention.
IEEE Trans. Emerg. Top. Comput. Intell., December, 2024
Team-wise effective communication in multi-agent reinforcement learning.
Auton. Agents Multi Agent Syst., December, 2024
SFANet: Spatial-Frequency Attention Network for Weather Forecasting.
CoRR, 2024
Emulating Full Client Participation: A Long-Term Client Selection Strategy for Federated Learning.
CoRR, 2024
CauDR: A causality-inspired domain generalization framework for fundus-based diabetic retinopathy grading.
Comput. Biol. Medicine, 2024
scTCA: a hybrid Transformer-CNN architecture for imputation and denoising of scDNA-seq data.
Briefings Bioinform., 2024
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
ANEDL: Adaptive Negative Evidential Deep Learning for Open-Set Semi-supervised Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Debiased Recommendation with User Feature Balancing.
ACM Trans. Inf. Syst., October, 2023
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling.
,
,
,
,
,
,
,
,
,
,
,
,
,
Nat. Mac. Intell., September, 2023
rcCAE: a convolutional autoencoder method for detecting intra-tumor heterogeneity and single-cell copy number alterations.
Briefings Bioinform., May, 2023
Contrastive-ACE: Domain Generalization Through Alignment of Causal Mechanisms.
IEEE Trans. Image Process., 2023
Efficient and accurate large library ligand docking with KarmaDock.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
Nat. Comput. Sci., 2023
CauDR: A Causality-inspired Domain Generalization Framework for Fundus-based Diabetic Retinopathy Grading.
CoRR, 2023
Invariant Learning via Probability of Sufficient and Necessary Causes.
CoRR, 2023
Meta Adaptive Task Sampling for Few-Domain Generalization.
CoRR, 2023
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning.
CoRR, 2023
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction.
CoRR, 2023
Invariant Learning via Probability of Sufficient and Necessary Causes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Learning Robust Classifier for Imbalanced Medical Image Dataset with Noisy Labels by Minimizing Invariant Risk.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Fast Non-Markovian Diffusion Model for Weakly Supervised Anomaly Detection in Brain MR Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Specify Robust Causal Representation from Mixed Observations.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning.
Proceedings of the International Conference on Machine Learning, 2023
CauSSL: Causality-inspired Semi-supervised Learning for Medical Image Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Traj-MAE: Masked Autoencoders for Trajectory Prediction.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
TieComm: Learning a Hierarchical Communication Topology Based on Tie Theory.
Proceedings of the Database Systems for Advanced Applications, 2023
RepMode: Learning to Re-Parameterize Diverse Experts for Subcellular Structure Prediction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Learning to select cuts for efficient mixed-integer programming.
Pattern Recognit., 2022
Weakly Supervised Disentangled Generative Causal Representation Learning.
J. Mach. Learn. Res., 2022
Structured Q-learning For Antibody Design.
CoRR, 2022
Treatment Effect Estimation with Unmeasured Confounders in Data Fusion.
CoRR, 2022
Generalizable Information Theoretic Causal Representation.
CoRR, 2022
Debiased Recommendation with User Feature Balancing.
CoRR, 2022
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-Based Policy Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022
2021
Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth.
CoRR, 2021
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms.
CoRR, 2021
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
DARING: Differentiable Causal Discovery with Residual Independence.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
Causal World Models by Unsupervised Deconfounding of Physical Dynamics.
CoRR, 2020
Disentangled Generative Causal Representation Learning.
CoRR, 2020
Decoder-free Robustness Disentanglement without (Additional) Supervision.
CoRR, 2020
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder.
CoRR, 2020
2018
Causal Inference on Multidimensional Data Using Free Probability Theory.
IEEE Trans. Neural Networks Learn. Syst., 2018
Confounder Detection in High-Dimensional Linear Models Using First Moments of Spectral Measures.
Neural Comput., 2018
2017
On the Relations of Theoretical Foundations of Different Causal Inference Algorithms.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2017 - 18th International Conference, Guilin, China, October 30, 2017
2016
Causal Discovery on Discrete Data with Extensions to Mixture Model.
ACM Trans. Intell. Syst. Technol., 2016
Causal Inference on Discrete Data via Estimating Distance Correlations.
Neural Comput., 2016
2013
U-Air: when urban air quality inference meets big data.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013
2012
Unsupervised Feature Selection for Multi-cluster Data via Smooth Distributed Score.
Proceedings of the Emerging Intelligent Computing Technology and Applications, 2012
Dual Locality Preserving Nonnegative Matrix Factorization for image analysis.
Proceedings of the 2012 IEEE International Conference on Granular Computing, 2012