Python implementation of adaptive spiking neural net proposed in Gutierrez and Deneve eLife 2019.
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.
pronouncing my family name, Dương: Vietnamese is a tonal language so it's hard to describe via text, but saying "Yuh-ng" will get you close. Most pronounce it like "Dew-ong"/"Dwong", which is also fine.
Simple code to save activations of a model’s intermediate layers.
A cool algorithm that adaptively approximates the column space of a matrix using random projections.
Simple implenetation of the RealNVP invertible neural network.
This short post will cover graphical intuition and PyTorch code for two different kinds of whitening: batch and instance.
A tutorial for a classic numerical linear algebra algorithm to find eigenvectors and values.
A Python implementation of the elegant algorithm introduced by Iain Murray et al. (2010).
What’s the best way to quantify and visualize distance between two positive definite matrices? Julia code included.