Dieterich Lawson Headshot

Dieterich Lawson

I am PhD student in computer science at Stanford University, advised by Scott Linderman. My recent work focuses on mechanistic models for neural data and learning algorithms for better statistical inference.

Email: dieterich.lawson@gmail.com

Selected publications

(full list)

Energy-Inspired Models: Learning with Sampler-Induced Distributions
Dieterich Lawson*, George Tucker*, Bo Dai, and Rajesh Ranganath
Neural Information Processing Systems (NeurIPS), 2019

Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
George Tucker, Dieterich Lawson, Shixiang Gu, Chris J Maddison
International Conference on Learning Representations (ICLR), 2019

Filtering Variational Objectives
Chris J. Maddison*, Dieterich Lawson*, George Tucker*, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, and Yee Whye Teh
Neural Information Processing Systems (NeurIPS), 2017

Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J Maddison, Dieterich Lawson, Jascha Sohl-Dickstein
NeurIPS 2017

Learning Hard Alignments with Variational Inference
Dieterich Lawson*, Chung-Cheng Chiu*, George Tucker*, Colin Raffel, Kevin Swersky, and Navdeep Jaitly
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018