← Authors

Zhitang Chen

20 papers · 2012–2026 · 10 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (40) πŸƒ Academic Marathon (12) 🐝 Cross-Pollinator (11) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) πŸ† Keyword Champion πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (108) πŸ“ˆ Trend Setter πŸ’Ž Century Club (18) πŸ”₯ Unstoppable (7) πŸš€ Conference Pioneer

Conferences

NIPS (4) AAAI (3) AISTATS (2) CVPR (2) ICML (2) IJCAI (2) UAI (2) ICLR (1) JMLR (1) PGM (1)

Top co-authors

Shengyu Zhu (6) Yanhui Geng (4) Xinwei Shen (3) Jianye Hao (3) Junlong Lyu (3) Shoubo Hu (3) Laiwan Chan (3) Jun Wang (2) Pascal Poupart (2) Kun Zhang (2)

Keywords

causal discovery (4) domain generalization (2) structural causal model (2) maximum mean discrepancy (2) online learning (2) causal inference (2) bayesian optimization (2) disentangled representation (2) gaussian process (2) weakly supervised learning (1) bayesian inference (1) variable selection (1) reinforcement learning (1) feature transformation (1) domain adaptation (1) variational inference (1) robust optimization (1) markov decision process (1) hypothesis testing (1) minimax optimization (1)

Papers

AΒ²Flow: Automating Agentic Workflow Generation via Self-Adaptive Abstraction Operators AAAI 2026
Boosting Cross-problem Generalization in Diffusion-Based Neural Combinatorial Solver via Inference Time Adaptation AAAI 2026
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models ICML 2024
FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract) IJCAI 2023
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs NIPS 2023
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network AAAI 2023
Reframed GES with a neural conditional dependence measure UAI 2022
Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates NIPS 2022
Out-of-Distribution Generalization With Causal Invariant Transformations CVPR 2022
Weakly Supervised Disentangled Generative Causal Representation Learning JMLR 2022
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models CVPR 2021
Ordering-Based Causal Discovery with Reinforcement Learning IJCAI 2021
Causal Discovery with Reinforcement Learning ICLR 2020
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit AISTATS 2019
Domain Generalization via Multidomain Discriminant Analysis UAI 2019
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning ICML 2018
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models NIPS 2018
Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016
Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings AISTATS 2016
Causal discovery with scale-mixture model for spatiotemporal variance dependencies NIPS 2012