Alexis David Jacq (alexis-jacq)

alexis-jacq

Geek Repo

Company:Google

Location:Paris

Home Page:https://alexis-jacq.github.io/

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Alexis David Jacq's repositories

Pytorch-Sketch-RNN

a pytorch implementation of https://arxiv.org/abs/1704.03477

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Pytorch-DPPO

Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286

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Pytorch-Tutorials

Pytorch tutorials for Neural Style transfert

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LOLA_DiCE

Pytorch implementation of LOLA (https://arxiv.org/abs/1709.04326) using DiCE (https://arxiv.org/abs/1802.05098)

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numpy_ARS

A 150-lines python code for Augmented Random Search (https://arxiv.org/abs/1803.07055) with numpy.

image_scaling

Some fast super resolution imaging algorithms

Pytorch-ChatBot

Pytorch implementation of "A Neural Conversational Agent" https://arxiv.org/pdf/1506.05869.pdf

Story_CoWriting

Short story co-creation with human and robot

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Pytorch_Policy_Search_Optimizer

A tool for optimizing RL policy modules based on random search

thelen2003

muscle simulator for mujoco tendons

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Learning_from_a_Learner

Implements code from LfL paper (http://proceedings.mlr.press/v97/jacq19a/jacq19a.pdf).

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lola

Code release for Learning with Opponent-Learning Awareness and variations.

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episodic-curiosity

Tensorflow/Keras code and trained models for Episodic Curiosity Through Reachability

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signals

Real-time human body signal recognition and generation

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the-incredible-pytorch

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.

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torch-rl

A recurrent, multi-process and readable PyTorch implementation of the deep reinforcement algorithms A2C and PPO

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bullet3

Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.

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DeepMind-Atari-Deep-Q-Learner

The original code from the DeepMind article + my tweaks

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gym-minigrid

Minimalistic gridworld environment for OpenAI Gym

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opencv

Open Source Computer Vision Library

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osim-rl

Reinforcement learning environments with musculoskeletal models

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paiss

NLE practical session for PAISS 2018

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planet

Deep Planning Network: Control from pixels by latent planning with learned dynamics

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pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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TH

Standalone C TH library

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