This repo implements AlphaDOGS algorithm to optimize the objective function computed from a time-averaged statistics.
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Updated
Jan 13, 2020 - Python
This repo implements AlphaDOGS algorithm to optimize the objective function computed from a time-averaged statistics.
Sampling based Model Predictive Control package for Model-Based RL research
Nevergrad Optimizer Benchmarking for 3D Performance Capture
This repository contains the official PyTorch implementation of the paper: "Learning Discrete Structured VAE using NES".
A simple implementation of SPSA with automatic learning rate tuning
A reimplementation of the derivative-free global optimization algorithm GLIS adjusted for the needs of the team
Object-Orientated Derivative-Free Optimisation
Python library for root-finding in one dimension
Statistical learning models library for blackbox optimization
Elo ratings for global black box derivative-free optimizers
deforce: Derivative-Free Algorithms for Optimizing Cascade Forward Neural Networks
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling
Benchmarking optimization solvers.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
OMADS - A blackbox optimization python package
0th order optimizers, gradient chaining, random gradient approximation
PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants (evolutionary algorithms/swarm-based optimizers/pattern search/...). [https://pypop.rtfd.io/]
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