bouthilx

ml-survey-2020

Results of the survey on machine-learning experimental methods at NeurIPS2019 and ICLR2020

orion

Asynchronous Distributed Hyperparameter Optimization for Deep Neural Networks

mahler

Orchestration engine for high latency systems and dynamic workflows

ml-method-video

aicamp-orion-example

Examples for the presentation at AICamp

bbo_challenge_starter_kit

Starter kit for the black box optimization challenge at Neurips 2020

bouthilx.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

carbon-tutorial

An app for the Carbon Design System tutorial

cluster-map

cpython

The Python programming language

cqueue

Message Queue Primitives

DEHB

emukit

A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

gym-minigrid

Minimalistic gridworld package for OpenAI Gym

hpo-testing

mahler.registry.mongodb

Mahler Registry Plugin using MongoDB

mila-docs

Mila technical documentation

milabench

Repository of training benchmarks

nox

Flexible test automation for Python

orion.algo.grid_search

A GridSearch plugin for Oríon

orion.algo.hyperband

Orion plugin of Hyperband algorithm

orion.algo.nomad

Nomad plugin for Oríon.

orion.algo.robo

A wrapper around the RoBO Bayesian Optimization Framework plugin for orion

orion.algo.skopt

Wrapper for scikit-optimize bayesian optimization

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

sample-space

scikit-optimize

Sequential model-based optimization with a `scipy.optimize` interface

test-integration

vision

Datasets, Transforms and Models specific to Computer Vision

website

Personal website