This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers"

Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020

Editorial venue for ML Reproducibility Challenge Accepted papers

Code for our Reproducibility Challenge Paper "On end-to-end 6DoF object pose estimation and robustness to object scale"

This is the official repository of the paper "Performance Comparison of Session-based Recommendation Algorithms based on Graph Neural Networks"

Replication of the novel Generative Adversarial Transformer.

Detection and attribution of climate change using deep learning

Learning the Underlying Physics of a Simulation Model of the Ocean's Temperature

A preliminary analysis into the effort required for reproducing computational science scholarly articles.

Assignments for COMP 551: Applied Machine Learning at McGill University

Variational data assimilation with deep prior

Code, data and results of a reproducibility experiment for the paper "Exploring the Representation of Word Meanings in Context" by Marcos Garcia.

Testing the Reproducibility of the paper: MixSeq. Under the assumption that macroscopic time series follow a mixture distribution, they hypothesise that lower variance of constituting latent mixture components could improve the estimation of macroscopic time series.

Reproducibility Challenge 2020 papers