f-IRL
eirli
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f-IRL
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Can you use the reward learned in generative adversarial imitation learning in order to train from scratch?
Code for https://arxiv.org/abs/2011.04709 found: https://github.com/twni2016/f-IRL
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How to pretrain a model on expert data?
Try using an imitation learning algorithm. Two popular options are MaxEnt IRL and GAIL. This repository has GAIL implementation and this repository has MaxEnt IRL and GAIL implementation. There are other implementations too that you can check out.
eirli
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Image Dataset from D4RL for Mujoco Tasks
I am not aware of any for DM control tasks. Might worth looking at this if you’re interested in other environments.
What are some alternatives?
Meta-SAC - Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020
calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
falken - Falken provides developers with a service that allows them to train AI that can play their games
dino - PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
imitation - Clean PyTorch implementations of imitation and reward learning algorithms
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
tianshou - An elegant PyTorch deep reinforcement learning library.
pytorch_sac_ae - PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
DI-drive - Decision Intelligence Platform for Autonomous Driving simulation.