research
∙
05/25/2023
Meta Adaptive Task Sampling for Few-Domain Generalization
To ensure the out-of-distribution (OOD) generalization performance, trad...
share
research
∙
03/21/2023
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning
Semi-supervised learning (SSL) methods assume that labeled data, unlabel...
research
∙
03/12/2023
Traj-MAE: Masked Autoencoders for Trajectory Prediction
Trajectory prediction has been a crucial task in building a reliable aut...
research
∙
03/06/2023
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction
Attaining the equilibrium state of a catalyst-adsorbate system is key to...
research
∙
03/03/2023
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning
Uncertainty estimation is a key factor that makes deep learning reliable...
research
∙
12/20/2022
RepMode: Learning to Re-parameterize Diverse Experts for Subcellular Structure Prediction
In subcellular biological research, fluorescence staining is a key techn...
research
∙
12/04/2022
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder
The success of deep learning is partly attributed to the availability of...
research
∙
11/28/2022
Learning From Good Trajectories in Offline Multi-Agent Reinforcement Learning
Offline multi-agent reinforcement learning (MARL) aims to learn effectiv...
research
∙
08/23/2022
Treatment Effect Estimation with Unmeasured Confounders in Data Fusion
In the presence of unmeasured confounders, we address the problem of tre...
research
∙
07/26/2022
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
Deriving a good variable selection strategy in branch-and-bound is essen...
research
∙
06/20/2022
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
Collaborative multi-agent reinforcement learning (MARL) has been widely ...
research
∙
12/20/2021
Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth
Recent studies have shown that introducing communication between agents ...
research
∙
06/02/2021
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms
Domain generalization aims to learn knowledge invariant across different...
research
∙
06/01/2021
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning
Centralized Training with Decentralized Execution (CTDE) has been a popu...
research
∙
05/28/2021
Learning to Select Cuts for Efficient Mixed-Integer Programming
Cutting plane methods play a significant role in modern solvers for tack...
research
∙
12/28/2020
Causal World Models by Unsupervised Deconfounding of Physical Dynamics
The capability of imagining internally with a mental model of the world ...
research
∙
07/02/2020
Decoder-free Robustness Disentanglement without (Additional) Supervision
Adversarial Training (AT) is proposed to alleviate the adversarial vulne...
research
∙
04/18/2020
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder
Learning disentanglement aims at finding a low dimensional representatio...
research
∙
03/21/2018
Causal Inference on Discrete Data via Estimating Distance Correlations
In this paper, we deal with the problem of inferring causal directions w...
research
∙
03/19/2018