Stars
Google Research
Pytorch Implementation of Neural Architecture Optimization
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Turn Python scripts into handouts with Markdown and figures
Code for the ICML 2019 paper 'Conditioning by adaptive sampling for robust design'
Google's Engineering Practices documentation
Evolutionary & genetic algorithms for Julia
A JuMP-based Nonlinear Integer Program Solver
NASBench: A Neural Architecture Search Dataset and Benchmark
Recursive task allocation approach to foraging in swarm robotics. ARGoS and ROS.
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search (ICML 2018)
Code for "High Dimensional Bayesian Optimization via Supervised Dimension Reduction"
Max-value Entropy Search for Efficient Bayesian Optimization
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
A Matlab package for computing the optimal mode decomposition (OMD) or dynamic mode decomposition (DMD).
Matlab interior point solver for quadratic programs
An open-source MATLAB® ADMM solver for partially decomposable conic optimization programs.
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
COSMO: Accelerated ADMM-based solver for convex conic optimisation problems (LP, QP, SOCP, SDP, ExpCP, PowCP). Automatic chordal decomposition of sparse semidefinite programs.
An implementation of FeUdal Networks for Hierarchical Reinforcement Learning as published : https://arxiv.org/abs/1703.01161
Deep Reinforcement Learning with pytorch & visdom
Data Structures for Optimization Models
An open-source C++ library developed and used at Facebook.
Code for paper 'Learning transferable cooperative behaviors in multi-agent teams' (ICML 2019)