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Hi 👋, I'm Frank Tian.

I am a graduate student at Nanjing University in China with a passion for exploring the development of artificial intelligence. Currently, I am fully immersed in research on reinforcement learning and its intersection with causal discovery and inference. Alongside my academic pursuits, I maintain a keen interest in physics and astronomy and seek to uncover ways to construct general artificial intelligence through natural laws.

You can contact with me by nju-mail or gmail, however the latter one is not checked often.

Honglong Tian's Projects

adarl-code icon adarl-code

Implementation codes and datasets used in ICLR'22 Spotlight paper AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning.

c-swm icon c-swm

Contrastive Learning of Structured World Models

causal-mbrl icon causal-mbrl

Toolkit of Causal Model-based Reinforcement Learning.

causalmbrl icon causalmbrl

Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning

ccit icon ccit

Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing

d4rl icon d4rl

A benchmark for offline reinforcement learning.

dreamerv2 icon dreamerv2

Pytorch implementation of Dreamer-v2: Visual Model Based RL Algorithm.

elegantrl icon elegantrl

Lightweight and scalable deep reinforcement learning using PyTorch. 🔥

emei icon emei

Emei is a toolkit for developing causal reinforcement learning algorithms.

gcit icon gcit

Conditional Independence Testing with Generative Adversarial Networks

intact icon intact

Identifiable aNd TrAnsferable Causal meTa World Model.

login-express icon login-express

实现了登陆注册功能的小项目,全部使用js和html完成,使用MongoDB作为数据库。欢迎star。

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