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activitylifecycle

al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

algorithms

Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms.

aml-real-time-ai

Easily deploy models to FPGAs for ultra-low latency with Azure Machine Learning powered by Project Brainwave

appengine_android_tutorial

asteroid

The PyTorch-based audio source separation toolkit for researchers

atlas

awesome-nilm

A curated resources of awesome NILM resources

christofernal

christofernal.github.io

coding-interview-university

A complete computer science study plan to become a software engineer.

cosmos

Algorithms that run our universe | Your personal library of every algorithm and data structure code that you will ever encounter | Ask us anything at our forum

custom-pooling-operation

Learn how to create a pooling operation from scratch using Pytorch (python) or building your own C++ extension.

demucs

Code for the paper Hybrid Spectrogram and Waveform Source Separation

disentanglement_lib

disentanglement_lib is an open-source library for research on learning disentangled representations.

disentangling-vae

Experiments for understanding disentanglement in VAE latent representations

dlbook_exercises

Exercises for the Deep Learning textbook at www.deeplearningbook.org

dnner

Deep Neural Networks Entropy from Replicas

ebooks

books

econishe

Econishe

entropy-audio-feature-pooling

Experiments on two audio classification tasks, investigating the behavior of feature pooling based on the maxent principle.

gnnpapers

Must-read papers on graph neural networks (GNN)

ibsgd

independent-mechanism-analysis

Code for the paper: "Independent mechanism analysis, a new concept?"

informationtheory

Documents for Information Theory used in Master of Logic course Information Theory at the UvA

kaggle-mercedes

kaggle-quora

learning-synthetic-data

Package to run learning experiments on synthetic datasets using dnner package for replica entropy computations

learning-to-learn

TensorFlow implementation of the paper "Learning to learn by gradient descent by gradient descent ( https://arxiv.org/abs/1606.04474 )"

lit

The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.