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Repository Index
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Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
- generative-adversarial-network
- artificial-intelligence
- pytorch
- machine-learning
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
- deep-reinforcement-learning
- pytorch
- reinforcement-learning
- machine-learning
Modularized Implementation of Deep RL Algorithms in PyTorch
- pytorch
- deep-reinforcement-learning
- dqn
- dueling-network-architecture
A brain that learns from live experience. System 1 by default: perception, memory, plasticity and action. Optional System 2 for self-observation and slow corrections.
- machine-learning
- embodied-ai
- online-learning
- python
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
- reinforcement-learning
- deep-learning
- pytorch
- pytorch-reinforcement-learning
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Ropedia W0: Scaling Loco-Manipulation World Models across Embodiments with Human Experience
- cross-embodiment
- human-data
- loco-manipulation
- world-models