Pytorch Implementation of the World Models paper from 2018.
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Updated
Jul 23, 2023 - Jupyter Notebook
Pytorch Implementation of the World Models paper from 2018.
Source code for Master's Thesis: Curiosity-driven Planning with Reinforcement Learning.
Create and test your own cell colonies!
VQ-VAE-based image tokenizer for model-based RL
Master's thesis project on learning stateful simulations with deep differentiable models. The focus is to train a neural network to simulate a game (PONG) end-to-end.
A reinforcement learning project for crowd-dynamics in a very narrow corridor
Original implementations of the VC-FB and MC-FB algorithms from "Zero-Shot Reinforcement Learning from Low Quality Data" by Jeen et. al (2024).
Flax Implementation of DreamerV3 on Crafter
Toward Multi Modality Language Model - implementation of GPT-4o/Project Astra
[NeurIPS 2021] Contrastive learning formulation of the active inference framework, for matching visual goal states.
A new version of world models using Echo-state networks and random weight-fixed CNNs
Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morgan AI Research, 2019)>.
Minimum viable reinforcement learning algorithms for your educational convenience.
We develop world models that can be adapted with natural language. Intergrating these models into artificial agents allows humans to effectively control these agents through verbal communication.
I GAVE GPT-4 EYES!
PyTorch World Model implementation with PPO.
Dreamer on JAX
Pytorch implementation of DreamerV2: Mastering Atari with Discrete World Models, based on the original implementation
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