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Tengyuan Liang
Bio
Statistics Theory (math.ST)
Reversible Gromov-Monge Sampler for Simulation-Based Inference
Randomization Inference When N Equals One
High-Dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
Detecting Weak Distribution Shifts via Displacement Interpolation
Interpolating Classifiers Make Few Mistakes
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
Universal Prediction Band via Semi-Definite Programming
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers
Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks
How Well Generative Adversarial Networks Learn Distributions
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