René Parlange's repositories

machine-learning-engineering-for-production-public

Public repo for DeepLearning.AI MLEP Specialization

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parlange.github.io

github.io | parlange

atari-rl

Atari - Deep Reinforcement Learning algorithms in TensorFlow

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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

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automl-in-action-notebooks

Jupyter notebooks for the code samples of the book "Automated Machine Learning in Action"

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deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

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Deep_reinforcement_learning_Course

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

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lenstronomy-tutorials

Extension modules to the lenstronomy software package

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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.

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ml-in-cosmology

A comprehensive list of published machine learning applications to cosmology

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nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

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pyHalo

A python toolkit for rendering populations of dark matter halos for gravitational lensing simulations

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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.

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conda-cuda

Guide to install cuda and cudnn with Anaconda

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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.

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gigalens

Gradient Informed, GPU Accelerated Lens modelling (GIGALens) -- a package for fast Bayesian inference on strong gravitational lenses.

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gravitational-lensing

Gravitational lensing course

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jax

JAX

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lenstronomy-surveys

Simulating strong gravitational lenses on LSST, DES, and Roman Space Telescope

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ml-notebooks

Colab/Jupyter noteboks on machine learning

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neural-subhalo-slope-data

Code for "Subhalo effective density slope measurements from HST strong lensing data with neural likelihood-ratio estimation"

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NeuralPLexer

NeuralPLexer: State-specific protein-ligand complex structure prediction with a multi-scale deep generative model

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paltas

Conduct simulation-based inference on strong gravitational lensing systems.

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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.

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strong_lensing_vit_resnet

Vision Transformers on Gravitational Lens Images

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systematic-review

Systematic Review of Machine Learning Methods for Strong Lens Detection

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Tensorflow-2-Reinforcement-Learning-Cookbook

Tensorflow 2 Reinforcement Learning Cookbook, published by Packt

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tensorflow-probability

Tensorflow Probability (TFP)

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ztf_sim

:telescope: Zwicky Transient Facility survey scheduler

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