Tutorials, assignments, and competitions for MIT Deep Learning related courses.
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Updated
Nov 5, 2022 - Jupyter Notebook
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
A curated list of awesome Deep Reinforcement Learning resources.
Pytorch code for NeurIPS-20 Paper "Object Goal Navigation using Goal-Oriented Semantic Exploration"
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
A collection of Deep RL algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.
Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)
Mirror Descent Policy Optimization
OpenAI团队的深度强化学习教程中文版
You can see a reference for Books, Articles, Courses and Educational Materials in this field. Implementation of Reinforcement Learning Algorithms and Environments. Python, OpenAI Gym, Tensorflow.
Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym
A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.
RLbox: Solving OpenAI Gym with TensorFlow
Implementation of Curiosity-Driven Exploration with PyTorch
Attend Before you Act: Leveraging human visual attention for continual learning
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