Guangyao (Stannis) Zhou

Researcher, Vicarious AI

stannis [AT] vicarious.com

About

I am an applied mathematician, and a researcher at Vicarious AI. I obtained my Ph.D. in applied math at Brown University, advised by Prof. Stuart Geman, and my bachelor degrees from Peking University.

My current research interests are in building compositional probabilistic generative models, and the associated inference and learning problems.

Publications

Most recent publications on Google Scholar.
indicates equal contribution.

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables

Miguel Lázaro-Gredilla, Wolfgang Lehrach, Nishad Gothoskar, Guangyao Zhou,
Antoine Dedieu, Dileep George

AAAI Conference on Artificial Ingelligence (AAAI) 2021

Mixed Hamiltonian Monte Carlo for mixed discrete and continuous variables

Guangyao Zhou

Advances in Neural Information Processing Systems (NeurIPS) 2020
Extended abstract accepted as talk at PROBPROG 2020

A detailed mathematical theory of thalamic and cortical microcircuits based on inference
in a generative vision model

Dileep George, Miguel Lázaro-Gredilla, Wolfgang Lehrach, Antoine Dedieu, Guangyao Zhou

bioRxiv 2020.09.09.290601

Capacities and efficient computation of first passage probabilities

Jackson Loper, Guangyao Zhou, Stuart Geman

Phys. Rev. E 102, 023304, 2020

Base-pair ambiguity and the kinetics of RNA folding

Guangyao Zhou, Jackson Loper, Stuart Geman

BMC Bioinformatics, 20(1):666, 2019

Sparse feature selection by information theory

Guangyao Zhou, Stuart Geman, Joachim M Buhmann

IEEE International Symposium on Information Theory (ISIT), 2014

L1-graph construction using structured sparsity

Guangyao Zhou, Zhiwu Lu, Yuxin Peng

Neurocomputing, 120:441-452, 2013

Vitæ

Full Resume in PDF.

Acknowledgement

This website uses the website design and template by Martin Saveski