chaochaolu Goto Github PK

followers: 34.0 following: 13.0 repos: 58.0 gists: 0.0

Name: Chaochao Lu

Type: User

Company: Shanghai AI Laboratory

Location: Shanghai, China

Blog: https://causallu.com/

Chaochao Lu's Projects

a-meta-transfer-objective-for-learning-to-disentangle-causal-mechanisms

Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"

a3c-continuous

Tensorflow implementation of the asynchronous advantage actor-critic (a3c) reinforcement learning algorithm for continuous action space

applied-reinforcement-learning

Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks

awesome-public-datasets

A topic-centric list of high-quality open datasets in public domains. Propose NEW data ☛☛☛PR☛☛☛

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

bayesian_benchmarks

A community repository for benchmarking Bayesian methods

bullet3

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

causal_inference_python_code

Python code for part 2 of the book Causal Inference, by Miguel Hernán and James Robins

causaldiscoverytoolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

causalinference

Causal Inference in Python

cbl-website

CBL website

cevae

Causal Effect Inference with Deep Latent-Variable Models

cs238_sepsis_rl

Learning to reinforcement learn and treating sepsis on the side

deep-reinforcement-learning-hands-on

Hands-on Deep Reinforcement Learning, published by Packt

deep-reinforcement-learning-papers-1

A list of papers and resources dedicated to deep reinforcement learning

deep_reinforcement_learning_course

Notebooks from our series of blogpost about Deep Reinforcement Learning

disentanglement_lib

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

dmm

Deep Markov Models

drl

Deconfounding Reinforcement Learning in Observational Settings

gcit

Conditional Independence Testing with Generative Adversarial Networks

gmps

Guided-Meta Policy Search

gmvae

Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

gym-cartpolemod

Modified CartPole-v0 OpenAI Gym environment with various noisy cases and Reinforcement Learning based controller

handful-of-trials

Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

iap-cidl

Causal Inference & Deep Learning, MIT IAP 2018

ivae

VAEs and nonlinear ICA: a unifying framework

learning_to_adapt

Learning to Adapt in Dynamic, Real-World Environment through Meta-Reinforcement Learning

maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

maml_rl

Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

chaochaolu Goto Github PK

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