Reverse Dependencies of botorch

The following projects have a declared dependency on botorch:

• aepsych — Adaptive experimetation for psychophysics
• atom-ml — A Python package for fast exploration of machine learning pipelines
• ax-platform — Adaptive Experimentation
• baybe — A Bayesian Back End for Design of Experiments
• beanmachine — Probabilistic Programming Language for Bayesian Inference
• beebo — Batched Energy-Entropy acquistion for Bayesian optimization
• blackboxopt — A common interface for blackbox optimization algorithms along with useful helpers like parallel optimization loops, analysis and visualization scripts.
• blopt — Beamline optimization with machine learning
• bloptools — Beamline optimization with machine learning
• bluesky-adaptive — Tools for writing adaptive plans
• bocoel — Bayesian Optimization as a Coverage Tool for Evaluating Large Language Models
• bofire — no summary
• bolift — BayesOPT with LIFT
• botorchex — no summary
• drl-model — DRL logic
• edbojz — Bayesian reaction optimization as a tool for chemical synthesis.
• gpplus — Python Library for Generalized Gaussian Process Modeling
• greattunes — Toolset for easy execution of Bayesian optimization for either step-by-step or closed-loop needs.
• harlow — Adaptive surrogate modelling
• hdbo-b — High-Dimentional Bayesian Benchmark (HDBO-B)
• invert4geom — Constrained gravity inversion to recover the geometry of a density contrast.
• jetto-mobo — no summary
• laplace-bayesopt — Bayesian optimization interface for the laplace-torch library
• lume-model — Data structures used in the LUME modeling toolset.
• moebius — Python package for optimizing peptide sequences using Bayesian optimization (BO)
• MolDAIS — Molecular Property Optimization with Molecular Descriptors over Actively Identified Subspaces
• nemo-bo — Multi-objective optimization of chemical processes with automated machine learning workflows
• nextorch — Experimental design and Bayesian optimization library in Python/PyTorch
• obsidian_apo — Automated experiment design and black-box optimization
• optuna-integration — Integration libraries of Optuna.
• petboa — Parameter Estimation using Bayesian Optimization
• pfns — PFNs made ready for BO
• pfns4bo — PFNs made ready for BO
• piglot — A package for the optimisation of numerical responses
• PyFemtet — Design parameter optimization using Femtet.
• pytorch-cortex — A modular architecture for deep learning systems.
• pytorch-dragon — A pytorch integrated Machine Learning / Deep learning utilities library
• pytorch-holo — Benchmarks for discrete sequence optimization
• rctorch — A Python 3 toolset for creating and optimizing Echo State Networks. This library is an extension and expansion of the previous library written by Reinier Maat: https://github.com/1Reinier/Reservoir
• sb-arch-opt — SBArchOpt: Surrogate-Based Architecture Optimization
• scioptim — collection and wrapper for different optimizer
• scorepyo — This is the scorepyo repository.
• sober-bo — Fast Bayesian optimization, quadrature, inference over arbitrary domain (discrete and mixed spaces) with GPU parallel acceleration based on GPytorch and BoTorch.
• summit — Tools for optimizing chemical processes
• svise — State estimation of a physical system with unknown governing equations
• syne-tune — Distributed Hyperparameter Optimization on SageMaker
• uq360 — Uncertainty Quantification 360
• veropt — Bayesian Optimisation for the Versatile Ocean Simulator (VEROS)
• VOPy — A framework for black-box vector optimization
• wdbo-algo — W-DBO Algotithm for Dynamic Bayesian Optimization
• zellij — A software framework for HyperParameters Optimization