René Parlange's repositories
machine-learning-engineering-for-production-public
Public repo for DeepLearning.AI MLEP Specialization
parlange.github.io
github.io | parlange
atari-rl
Atari - Deep Reinforcement Learning algorithms in TensorFlow
AutoML
Deep Reinforcement Learning for Efficient Neural Architecture Search (ENAS) in PyTorch, i.e., AutoML. Code based on the paper https://arxiv.org/abs/1802.03268
automl-in-action-notebooks
Jupyter notebooks for the code samples of the book "Automated Machine Learning in Action"
deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
Deep_reinforcement_learning_Course
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
lenstronomy-tutorials
Extension modules to the lenstronomy software package
ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
ml-in-cosmology
A comprehensive list of published machine learning applications to cosmology
nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
pyHalo
A python toolkit for rendering populations of dark matter halos for gravitational lensing simulations
ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
conda-cuda
Guide to install cuda and cudnn with Anaconda
get-started-with-JAX
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
gigalens
Gradient Informed, GPU Accelerated Lens modelling (GIGALens) -- a package for fast Bayesian inference on strong gravitational lenses.
gravitational-lensing
Gravitational lensing course
jax
JAX
lenstronomy-surveys
Simulating strong gravitational lenses on LSST, DES, and Roman Space Telescope
ml-notebooks
Colab/Jupyter noteboks on machine learning
neural-subhalo-slope-data
Code for "Subhalo effective density slope measurements from HST strong lensing data with neural likelihood-ratio estimation"
NeuralPLexer
NeuralPLexer: State-specific protein-ligand complex structure prediction with a multi-scale deep generative model
paltas
Conduct simulation-based inference on strong gravitational lensing systems.
Physics-Informed-Features-For-Dark-Matter-Morphology
The Physics Informed Features module, created under the international Google Summer of Code program, is a complex tool designed for the generation and manipulation of data in relativistic gravitational lensing studies.
strong_lensing_vit_resnet
Vision Transformers on Gravitational Lens Images
systematic-review
Systematic Review of Machine Learning Methods for Strong Lens Detection
Tensorflow-2-Reinforcement-Learning-Cookbook
Tensorflow 2 Reinforcement Learning Cookbook, published by Packt
tensorflow-probability
Tensorflow Probability (TFP)
ztf_sim
:telescope: Zwicky Transient Facility survey scheduler