Stochastic gradient Markov chain Monte Carlo
PyTorch implementation and explanation of SGD MCMC sampling w/ Langevin or Hamiltonian dynamics.
I'm a PhD student at NYU studying computational models of neural population adaptation, supervised by Eero Simoncelli and David Heeger. My dissertation focuses on adaptive gain control in recurrent neural networks, and developing statistical methods for analyzing artificial and biological neural repesentations.
In the Summer of 2022, I was a PhD Intern on the Open Codecs team at Google, Mountain View, CA. My research project was on adaptive auto-encoders and efficient nonlinear transforms for next-generation video compression.
I'm a born-and-raised Canadian 🍁. I received my BSc in Physiology and Physics at McGill University, where I began working on what would eventually become my MSc obtained from the University of Western Ontario (our lab migrated), modeling neural correlates of visuo-spatial attention in prefrontal cortex under the supervision of Julio Martinez-Trujillo.
Outside of research, I enjoy playing jazz guitar, cycling, and running.
PyTorch implementation and explanation of SGD MCMC sampling w/ Langevin or Hamiltonian dynamics.