Library for Jacobian descent with PyTorch. It enables optimization of neural networks with multiple losses (e.g. multi-task learning).

This contains experiments on training a TRM architecture using Jacobian Descent.

Hierarchical Reasoning Model Official Release

A Collection of Variational Autoencoders (VAE) in TorchJD.

TorchJD implementation of GAN with gradient reversal layer

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

An Easy To Use Particle Emitter

Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

Time should be taken seer-iously

Disentanglement library for PyTorch

The project is the main grading item of the course.

EPFL Machine Learning Course, Fall 2018

Python Data. Leaflet.js Maps.

Address Book sample application (Level 4)

A sample repo for practicing how to create Pull Requests

ADA 2017 final exam - CS401 @ EPFL