Zhitang Chen
20 papers · 2012–2026 · 10 conferences · across top CS/AI conferences
Achievements
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🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (12)
🐣
Hot Topic Early Bird
🌉
Interdisciplinary Bridge
🌍
Conference Polyglot
(10)
🏆
Keyword Champion
🏆
Grand Slam
🗃️
Keyword Collector
(108)
📈
Trend Setter
💎
Century Club
(18)
🔥
Unstoppable
(7)
🚀
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
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
A²Flow: 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