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← Authors

Yao Xie

27 papers · 2015–2025 · 5 conferences · across top CS/AI conferences

Achievements

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+9 more ↓ πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (10) πŸ—ΊοΈ Taxonomy Completionist (44)
🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) πŸ‘‘ Triple Crown ⚑ Prolific Year (6) πŸ’Ž Century Club (27) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (102)

Conferences

NIPS (8) ICML (7) AISTATS (6) ICLR (4) CVPR (2)

Top co-authors

Chen Xu (6) Xiuyuan Cheng (6) Shixiang Zhu (5) Liyan Xie (4) RUI GAO (3) Jie Wang (3) Shuang Li (3) Le Song (3) Minghe Zhang (3) Song Wei (2)

Keywords

neural network (3) distributionally robust optimization (2) two-sample test (2) kernel methods (2) event prediction (2) uncertainty quantification (2) change-point detection (2) regret bound (2) hawkes process (2) conformal prediction (2) prediction interval (2) generative model (2) policy gradient (1) model misspecification (1) neural tangent kernel (1) change detection (1) image restoration (1) 3d reconstruction (1) stochastic optimization (1) robust statistics (1)

Papers

Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions ICML 2025 Computing high-dimensional optimal transport by flow neural networks AISTATS 2025 Consistency Posterior Sampling for Diverse Image Synthesis CVPR 2025 Kernel-based Optimally Weighted Conformal Time-Series Prediction ICLR 2025 Nonlinear Sequence Embedding by Monotone Variational Inequality ICLR 2025 Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances ICML 2025 Conformal prediction for multi-dimensional time series by ellipsoidal sets ICML 2024 Sequential Predictive Conformal Inference for Time Series ICML 2023 Contextual Stochastic Bilevel Optimization NIPS 2023 Normalizing flow neural networks by JKO scheme NIPS 2023 Spatio-temporal point processes with deep non-stationary kernels ICLR 2023 Distributionally robust weighted k-nearest neighbors NIPS 2022 Two-Sample Test with Kernel Projected Wasserstein Distance AISTATS 2022 Neural Spectral Marked Point Processes ICLR 2022 Inferring serial correlation with dynamic backgrounds ICML 2021 Goodness-of-Fit Test for Mismatched Self-Exciting Processes AISTATS 2021 Conformal prediction interval for dynamic time-series ICML 2021 Deep Fourier Kernel for Self-Attentive Point Processes AISTATS 2021 Neural Tangent Kernel Maximum Mean Discrepancy NIPS 2021 Temporal Logic Point Processes ICML 2020 Uncertainty Quantification for Inferring Hawkes Networks NIPS 2020 Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit AISTATS 2019 Learning Transformation Synchronization CVPR 2019 Learning Temporal Point Processes via Reinforcement Learning NIPS 2018 Robust Hypothesis Testing Using Wasserstein Uncertainty Sets NIPS 2018 Nearly second-order optimality of online joint detection and estimation via one-sample update schemes AISTATS 2018 M-Statistic for Kernel Change-Point Detection NIPS 2015