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adversarialnetspapers

The classical papers and codes about generative adversarial nets

anchored_ensembling

awesome-deep-learning-papers

The most cited deep learning papers

awesome-deep-vision

A curated list of deep learning resources for computer vision

baselines

A collection of baselines for the MineRL environment/datasets & the NeurIPS 2019 MineRL competition

categorical_dqn

char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

cpp2py_data

cpprl

crypto

cs231n

ddpg

Tensorflow implementation of Deep Deterministic Policy Gradients

decima-sim

Learning Scheduling Algorithms for Data Processing Clusters

deep-blogs

A curated lists of self-taught materials including research blogs

deep-tutorials

A collection of tutorials from Deep Learning conferences.

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

gym

A toolkit for developing and comparing reinforcement learning algorithms.

hmfaysal-omega-theme

HMFAYSAL OMEGA is a minimalist, beautiful, responsive theme for Jekyll designed for writers who want their content to take front and center.

homework

Assignments for CS294-112.

installation-1080ti

Installation on NVIDIA graphic driver (1080ti)

learn2branch

Exact Combinatorial Optimization with Graph Convolutional Neural Networks (NeurIPS 2019)

magnet

MAGNet: Multi-agents control using Graph Neural Networks

models

Models built with TensorFlow

modulabs_log

Modulabs SafeAI Lab logs

oh-my-zsh

A delightful community-driven (with 1,100+ contributors) framework for managing your zsh configuration. Includes 200+ optional plugins (rails, git, OSX, hub, capistrano, brew, ant, php, python, etc), over 140 themes to spice up your morning, and an auto-update tool so that makes it easy to keep up with the latest updates from the community.

paper-notes

Collections of notes related to machine learning papers

papers

practical_rl

A course in reinforcement learning in the wild

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration