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Machine Learning Engineering Open Book
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Deep learning for dummies. All the practical details and useful utilities that go into working with real models.
Foundation Models for Time Series
code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".
Self-supervised contrastive learning for time series via time-frequency consistency
Materials for Mathematical Tools for Neuroscience course at Harvard (Neurobio 212)
Repository on the collaborative IVADO medical imaging project between the Mila and NeuroPoly labs.
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series, from ServiceNow Research
Tools to connect to and interact with the Mila cluster
Benchmarks for Out-of-Distribution Generalization in Time Series Tasks
Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation
Example of Dense Associative Memory training on MNIST
Animation of the motion a double-pendulum. Both Julia and Python versions of the code are given.
Official reference implementation of dynamics contrastive learning (DCL).
Support material for MAT6115, Université de Montréal, Fall 2018
Library that provides metrics to assess representation quality
A graduate-level introduction to reinforcement learning as a framework for modeling, optimization, and control, connecting dynamic models, data, and applications beyond standard benchmarks.
2 day workshop on advanced topics in M/EEG analyis using mne python
T-PHATE manifold learning of brain state dynamics
Julia implementation of Liquid State Machine