Deep Reinforcement learning based tumour localisation
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Updated
Jun 26, 2018 - Python
Deep Reinforcement learning based tumour localisation
Upside-Down Reinforcement Learning (⅂ꓤ) implementation in PyTorch. Based on the paper published by Jürgen Schmidhuber.
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
Distributed PyTorch implementation of D4PG with ray. Using a SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.
Implementing Deep Reinforcement Learning Algorithms in Python for use in the MuJoCo Physics Simulator
The DDPG algorithm incorporates Actor-Critic Deep Learning Agent for solving continuous action reinforcement learning problems.
Implementation of Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings (NeurIPS, 2021) in Python
PPO algorithm implemetation for TF 2.8.0
Deep Reinforcement Learning: Continuous Control. Solve the Unity ML-Agents Reacher Environment.
Deliverables relating to the Advanced Reinforcement Learning University Unit
Pytorch implementation of Deep Deterministic Policy Gradients (DDPG)
Pytorch implementation of twin delayed deep deterministic policy gradients (TD3)
Pytorch implementation of Proximal Policy Optimization (PPO) for continuous action spaces
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