A lightweight Unity asset for running powerful Bayesian optimization. It supports practical human-in-the-loop workflows where the optimizer proposes parameter values, collects user feedback as objective scores, updates the model, and recommends the next design iteration.

Probability-density-based deep learning paradigm for the fuzzy design of functional metastructures. Research AAAS & NeurIPS ML4PS.

A pipeline to generate user-preferred photo-realistic avatars using stable-diffusion and bayesian-optimization.

Hyperpatameter Bayesian Optimization for Image Classification in PyTorch

Demonstrating the use of Prefect to orchestrate the creation of machine learning surrogate models as applied to mechanistic crop models.

An introduction to Bayesian optimization with an example of accelerator tuning task.

Practical CSV-backed Bayesian optimisation campaign toolkit with Python, CLI, notebooks, and a local Streamlit workbench. Supports mixed variables, constraints, review, replicates, cost-aware workflows, and coupled multi-objective qLogEHVI campaigns.

Uncertainty-aware Labelled Augmentations for High Dimensional Latent Space Bayesian Optimisation

Optimization of light-by-light scattering scenarios with BoTorch engine.

A concept-first repository of Jupyter notebooks tracing a path from PyTorch fundamentals to Bayesian Optimisation, designed both as a structured learning journey and as clear, self-contained tutorials for others.

Testing submission of AWS batch jobs using BoTorch (via Ax) and TorchX for neural architecture search

This repository applies Machine Learning to Quantum Optimal Control (QOC) for preparing the highly entangled Greenberger–Horne–Zeilinger (GHZ) state.

Code for the paper: Wasserstein enabled Bayesian optimization of composite functions.

Bayesian Optimization framework for CO₂ mineralization using ferrochrome steel slag. Bachelor thesis, RWTH Aachen (AVT.SVT), 2025.

A BoTorch-powered human-in-the-loop workflow for structured WorldQuant BRAIN alpha experimentation.

Async Bayesian-optimization controller with a persistent Slurm GPU worker pool

Experimental DoE + Bayesian Optimization with Domain Knowledge injection for chemistry/materials labs

Bayesian Optimisation with Decoupled Evaluations

OptunaのBoTorchSamplerのためのcandidates_funcの実装例および実験管理