Yao Xie
27 papers · 2015–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (49) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Champion
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Triple Crown
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(5)
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Century Club Β· Bronze
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Trend Setter
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(138)
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Research topics
Machine Learning
(23)
Optimization & Theory
(17)
Core Methods
(12)
Mathematics & Optimization
(10)
Learning Types
(7)
Deep Learning
(6)
Optimization
(6)
Artificial Intelligence
(5)
Data Science & Analytics
(5)
Mathematics
(5)
Methods
(5)
Computer Vision
(3)
Architectures
(3)
Core AI
(3)
Generation
(2)
Keywords
conformal prediction
(4)
neural network
(4)
hawkes process
(3)
uncertainty quantification
(3)
kernel methods
(3)
event prediction
(2)
non-stationary kernel
(2)
generative model
(2)
prediction interval
(2)
regret bound
(2)
time series forecasting
(2)
representation learning
(2)
change point detection
(2)
quantile regression
(2)
distributionally robust optimization
(2)
two-sample test
(2)
point process
(2)
intensity function
(2)
optimal transport
(2)
change detection
(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
Contextual Stochastic Bilevel Optimization
NeurIPS 2023
Normalizing flow neural networks by JKO scheme
NeurIPS 2023
Sequential Predictive Conformal Inference for Time Series
ICML 2023
Spatio-temporal point processes with deep non-stationary kernels
ICLR 2023
Distributionally robust weighted k-nearest neighbors
NeurIPS 2022
Neural Spectral Marked Point Processes
ICLR 2022
Two-Sample Test with Kernel Projected Wasserstein Distance
AISTATS 2022
Conformal prediction interval for dynamic time-series
ICML 2021
Deep Fourier Kernel for Self-Attentive Point Processes
AISTATS 2021
Goodness-of-Fit Test for Mismatched Self-Exciting Processes
AISTATS 2021
Inferring serial correlation with dynamic backgrounds
ICML 2021
Neural Tangent Kernel Maximum Mean Discrepancy
NeurIPS 2021
Temporal Logic Point Processes
ICML 2020
Uncertainty Quantification for Inferring Hawkes Networks
NeurIPS 2020
Learning Transformation Synchronization
CVPR 2019
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit
AISTATS 2019
Learning Temporal Point Processes via Reinforcement Learning
NeurIPS 2018
Nearly second-order optimality of online joint detection and estimation via one-sample update schemes
AISTATS 2018
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
NeurIPS 2018
M-Statistic for Kernel Change-Point Detection
NeurIPS 2015