Found 56; showing 48
slides and notebooks for tutorials and pitches
A package to analyse calcium imaging data recorded with the Miniscope.
Deep Learning EEG Playground
Spinal cord gray matter segmentation using deep dilated convolutions.
Axon/Myelin segmentation using Deep Learning
Ivado École d'hiver IVADO/MILA en apprentissage profond 2018
Let's explore how we can extract text from forms
ImplementAI Workshop on Deep NLP for Question Generation
A PyTorch implementation of OpenAI's REPTILE algorithm
Laboratoires du cours GLO-4030/GLO-7030
Automatically detect paper-based form fields
Understanding and visualizing PyTorch Batching with LSTM
WPS processes for climate model data, indices and extreme events
minc_keras is a code base that was developped during a hackathon to facillitate the implementation of deep learning models for brain imaging with the Keras package.
A place to host my ongoing analysis of Montreal commute data from the Montreal Open Data Portal
Attributing predictions made by the Inception network using the Integrated Gradients method
Code to analyse structural covariance brain networks using python.
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"
Introduction to Scientific Computing 🦊
AI-ON Consciousness Prior
categorical variational autoencoder using the Gumbel-Softmax estimator
http://nlp.seas.harvard.edu/2018/04/03/attention.html
Neural Turing Machines (NTM) - PyTorch Implementation
Pangeo website + discussion of general issues related to the project.
DEPRECATED - DO NOT USE
A repository to host extended examples and tutorials
Various tutorials given for welcoming new students at MILA.
Trust Region Policy Optimization with TensorFlow and OpenAI Gym
Detectorch - detectron for PyTorch
PyTorch and Tensorflow functional model definitions
Pelican plugin for blogging with Jupyter/IPython Notebooks
3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.
Fast, flexible and easy to use probabilistic modelling in Python.
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
LSTM trained on the first five ASOIAF/GOT books
IPython kernel for Torch with visualization and plotting
Notes for Fastai Deep Learning Course
A collection of infrastructure and tools for research in neural network interpretability.
Learn Deep Reinforcement Learning in Depth in 60 days
Chess reinforcement learning by AlphaGo Zero methods.
Datasets, Transforms and Models specific to Computer Vision
A crash course in six episodes for software developers who want to become machine learning practitioners.
Deep learning software for colorizing black and white images with a few clicks.
An interactive book on deep learning. Much easy, so MXNet. Wow.
Image augmentation library in Python for machine learning.