Alexia Jolicoeur-Martineau

Deep-learning-with-cats. Deep learning with cats (^._.^)

RelativisticGAN. Code for replication of the paper "The relativistic discriminator: a key element missing from standard GAN"

MaximumMarginGANs. Code for paper: "Support Vector Machines, Wasserstein's distance and gradient-penalty GANs maximize a margin"

AdversarialConsistentScoreMatching. Code for paper "Adversarial score matching and improved sampling for image generation"

score_sde_fast_sampling. Repository for the "Gotta Go Fast When Generating Data with Score-Based Models" paper

relativistic-f-divergences. Code from paper "On Relativistic f-divergences" (http://arxiv.org/abs/1901.02474)

Generative-model-most-similar-images. Function that output the 5 most similar training (real) images to the given generated (fake) images.

GANsBeyondDivergenceMin. Code for replication of the paper "GANs beyond divergence minimization"

LEGIT. An R package for the Latent Environmental & Genetic InTeraction (LEGIT) model

BayesTreePrior. R package for the simulation of the prior distribution of bayesian trees by Chipman et al. (1998).

score_sde. Official code for Score-Based Generative Modeling through Stochastic Differential Equations

deep-symbolic-optimization. Source code for deep symbolic optimization.

LEGIT_SAS. SAS macros for the Latent Environmental & Genetic InTeraction (LEGIT) model

machine-learning-interview-enlightener. This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

moses_fixed. Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

AlexiaJM.github.io. HTML

BigGAN-PyTorch. The author's officially unofficial PyTorch BigGAN implementation.

Vid-ODE. Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation

Presentations. TeX

torch-linear-assignment. Batch computation of the linear assignment problem on GPU.

guided-diffusion. Python

saspy. A Python interface module to the SAS System. It works with Linux, Windows, and mainframe SAS. It supports the sas_kernel project (a Jupyter Notebook kernel for SAS) or can be used on its own.

GxETesting. Code to replicate analyses from the paper "Distinguishing differential susceptibility, diathesis-stress and vantage sensitivity: beyond the single gene and environment model". See preprint: https://psyarxiv.com/27uw8.

generative-reversible. Jupyter Notebook

score_sde_pytorch. PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

STaSy_iris. Official code for "STaSy: Score-based Tabular data Synthesis", ICLR 2023

lavaan. an R package for structural equation modeling and more

conditional-flow-matching. TorchCFM: a Conditional Flow Matching library

megablocks. Python

dciknn_cuda. This is the CUDA GPU implementation + Python interface (using PyTorch) of DCI. The paper can be found at https://arxiv.org/abs/1512.00442.

ffcv. FFCV: Fast Forward Computer Vision (and other ML workloads!)