← Authors

Furui Liu

17 papers · 2021–2026 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (3) πŸƒ Academic Marathon (5) 🌈 Renaissance Researcher (9) πŸ—ΊοΈ Taxonomy Completionist (42) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) ⚑ Prolific Year (8) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (93) πŸ’Ž Century Club (16)

Conferences

AAAI (6) NIPS (4) CVPR (2) ICCV (2) ICML (2) JMLR (1)

Top co-authors

Guangyong Chen (5) Pheng-Ann Heng (4) Kun Kuang (4) Fei Wu (3) Yiming Wang (3) Leong Hou U (3) Jianye Hao (2) Kaiyan Zhao (2) Jiaze Wang (2) Xinwei Shen (2)

Research topics

Machine Learning (1) Privacy (1)

Keywords

causal inference (7) disentangled representation (2) exploration bonus (2) backdoor confounding (2) bisimulation metric (2) semi-supervised learning (2) structural causal model (2) intrinsic reward (2) credit assignment (2) evidential deep learning (2) multi-agent reinforcement learning (2) state discrepancy (2) reinforcement learning (2) trajectory prediction (1) autonomous driving (1) weakly supervised learning (1) medical imaging (1) metric learning (1) uncertainty quantification (1) out-of-distribution generalization (1)

Papers

DSAP: Enhancing Generalization in Goal-Conditioned Reinforcement Learning AAAI 2026
ANEDL: Adaptive Negative Evidential Deep Learning for Open-Set Semi-supervised Learning AAAI 2024
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus NIPS 2024
Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples AAAI 2024
DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems AAAI 2024
Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation AAAI 2023
Traj-MAE: Masked Autoencoders for Trajectory Prediction ICCV 2023
Invariant Learning via Probability of Sufficient and Necessary Causes NIPS 2023
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning ICML 2023
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning AAAI 2023
Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric NIPS 2023
RepMode: Learning to Re-Parameterize Diverse Experts for Subcellular Structure Prediction CVPR 2023
CauSSL: Causality-inspired Semi-supervised Learning for Medical Image Segmentation ICCV 2023
Weakly Supervised Disentangled Generative Causal Representation Learning JMLR 2022
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning ICML 2022
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder NIPS 2022
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models CVPR 2021