A Java package for scientific computing
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Updated
May 22, 2018 - Java
A Java package for scientific computing
Implementations of optimization techniques, sampling methods and evolutionary algorithms
Benchmark for Biophysical Sequence Optimization Algorithms
Implementation of various Bayesian Optimization algorithms
Multivariable control strategy for a reactor system, efficient global solution method for a reaction system and rocket, solution methods for two approximate formulations of the Bayesian optimal experiment design (OED) problem, optimal control approach for a cold plasma system.
Here we visualize the need for robust BO against an adversary. Clearly the optimum design point changes depending the uncertain parameter x, so we should identify a region for which the decision variable x resides in an optimal region.
Code repository of Embedded Bandits for Large-Scale Black-Box Optimization (AAAI'17)
Multivariable Numerical Optimization
Optimising HSD components (e.g. LVDS, ECL, CML) parameters using Bayesian Optimisation
Black-Box optimization of a rotor's shape using Projected Gradient Descent
Safe Explorative Bayesian Optimization -- Towards Personalized Treatments in Plasma Medicine
Exploratory Data Analysis of Random Search, CMA, and PSO Optimisation Algorithms for Facility Location Problem
A collection and visualization of single objective black-box functions for optimization benchmarking.
Implementation of the (μ/μ,λ)-Evolution Strategy (ES) with Search Path algorithm in C++
Code for executing virtual experiments with intelligent bet-and-run strategies for optimization, which efficiently utilize a total computational budget for getting good results by first starting n runs and after some time pick one of them to continue for the remaining budget.
Object-Orientated Derivative-Free Optimisation
A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).
Pytorch based reimplementation of COMS: Conservative Objective Models for Effective Offline Model-Based Optimization.
Derivative-free solver for the minimization of a function over the convex hull of a set of vectors
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