1280 Open source projects that are alternatives of or similar to Deep Cfr

ICCV2019 - A painting AI that can reproduce paintings stroke by stroke using deep reinforcement learning.

Complete-Life-Cycle-of-a-Data-Science-Project

Julia port of the Python autograd package.

Python Adaptive Signal Processing

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

Pytorch implementation of Block Neural Autoregressive Flow

A PyTorch implementation of Rainbow DQN agent

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Code for reproducing Flow ++ experiments

A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost.

AI trained using Genetic Algorithm and Deep Learning to play the game of snake

Learning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)

Chess reinforcement learning by AlphaGo Zero methods.

Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

Resources on various topics being worked on at IvLabs

Code for Java Deep Learning Cookbook

Forex trading simulator environment for OpenAI Gym, observations contain the order status, performance and timeseries loaded from a CSV file containing rates and indicators. Work In Progress

A vulnerable iOS App with Security Challenges for the Security Researcher inside you.

A list of papers on system design.

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

Code for "Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner" in ICCV 2017

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

Telegram Open Network research group. Telegram: https://t.me/ton_research

Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation

🃏 OpenAI Gym No Limit Texas Hold 'em Environment for Reinforcement Learning

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.

A structured implementation of MuZero

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

self-studying the Sutton & Barto the hard way

Various CNN models for CIFAR10 with Chainer

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

machine learning and deep learning tutorials, articles and other resources

🚗 Rocket League Distributed Deep Reinforcement Learning Bot

A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).

Trading environnement for RL agents, backtesting and training.

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Computational Cognitive Neuroscience, Fourth Edition

Discovering Neural Wirings (https://arxiv.org/abs/1906.00586)

OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.

Machine Learning for High Energy Physics.

Implementation of selected reinforcement learning algorithms in Tensorflow. A3C, DDPG, REINFORCE, DQN, etc.

A high-performance distributed training framework for Reinforcement Learning

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

🎓 Tidy tools for academics

🛠 All-in-one web-based IDE specialized for machine learning and data science.

A simple interface to instantiate Reinforcement Learning environments with SUMO for Traffic Signal Control. Compatible with Gym Env from OpenAI and MultiAgentEnv from RLlib.

Coding Demos from the School of AI's Move37 Course

A list of the top 10 computer vision papers in 2020 with video demos, articles, code and paper reference.

RObust document image BINarization

A tool for automatic phoneme transcription

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

An easy-to-use interface for measuring uncertainty and robustness.

Reinforcement Learning in Keras on VizDoom

A comprehensive autonomous decentralized systems framework for AI control architects.

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...