epignatelli/helx

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10
Rank 1,807,489 (Top 36 %)
Language
Python
License
Apache License 2.0
Created almost 4 years ago
Updated 9 months ago

epignatelli/helx

epignatelli

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Interoperating between (Deep) Reiforcement Learning libraries

navix

Accelerated minigrid environments with JAX

discovering-reinforcement-learning-algorithms

A Jax/Stax implementation of the general meta learning paper: Oh, J., Hessel, M., Czarnecki, W.M., Xu, Z., van Hasselt, H.P., Singh, S. and Silver, D., 2020. Discovering reinforcement learning algorithms. Advances in Neural Information Processing Systems, 33.

reinforcement-learning-an-introduction

A python implementation of the concepts in the book "Reinforcement Learning: An Introduction" by R.S. Sutton and A. G. Barto.

Jupyter Notebook

scalable-recognition-with-a-vocabulary-tree

A python implementation of the paper "Scalable Recognition with a Vocabulary Tree, D. Nister, H. Stewenius, 2006"

Jupyter Notebook

human-level-control-through-deep-reinforcement-learning

A jax/stax implementation of: Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A.A., Veness, J., Bellemare, M.G., Graves, A., Riedmiller, M., Fidjeland, A.K., Ostrovski, G. and Petersen, S., 2015. Human-level control through deep reinforcement learning. nature, 518(7540), pp.529-533.

TensorflowVisual

Building tensorflow graphs and running deep learning predictions from your favourite visual programming interface

cardiax

A python implementation of the fenton karma model using fourth order accuracy central finite difference method, euler update scheme, and jax

Jupyter Notebook

jax_enums

A Jax-compatible enumerable.

rainbow-drl

This is a python JAX implementation of the paper: Rainbow: Combining improvements in deep reinforcement learning, by M. Hessel et al. In Thirty-Second AAAI Conference on Artificial Intelligence.

Jupyter Notebook

normalising_flows

A pytorch implementation of the most commonly used normalising flows.

jaxboard

model-based-rl-for-atari

A python JAX implementation of the paper: Kaiser, L., Babaeizadeh, M., Milos, P., Osinski, B., Campbell, R.H., Czechowski, K., Erhan, D., Finn, C., Kozakowski, P., Levine, S. and Mohiuddin, A., 2019. Model-based reinforcement learning for atari. arXiv preprint arXiv:1903.00374.

OpenRGB

lfrl

Jupyter Notebook

LMaaS

Language Models as a Service