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.

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.

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

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

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.

This repository combines Machine Learning with the Variational Quantum Eigensolver (VQE), a hybrid quantum-classical algorithm for estimating ground state energies in quantum systems, useful in quantum chemistry and physics.

Interactive Bayesian optimization for expensive black-box functions, with a human in the loop. Developed as a capstone project for the Imperial College Machine Learning & AI certificate.

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

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

Bayesian Optimisation with Decoupled Evaluations