7 citations · 8 across the 5 of their papers we have counts for
5 papers
Scalable Bayesian Optimization of Composite Functions for Image-Based Inverse Problems in Materials Characterization
Dasol Yoon, Poompol Buathong, Chia-Hao Lee +3
Estimating physical parameters from scientific images is a common inverse problem in materials characterization that often relies on expensive physics-based simulations. In electro…
Better Protein Function Prediction by Modeling Survivorship Bias
Zhongmou Chao, Poompol Buathong, Ekaterina Selivanovitch +2
Protein sequence data from nature exhibits survivorship bias: we only observe data from those organisms that survive and reproduce, while non-functional protein mutations are elimi…
Fast Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Peter I. Frazier
Bayesian optimization of function networks (BOFN) is a framework for optimizing expensive-to-evaluate objective functions structured as networks, where some nodes' outputs serve as…
Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Jiayue Wan, Raul Astudillo +3
Bayesian optimization is a powerful framework for optimizing functions that are expensive or time-consuming to evaluate. Recent work has considered Bayesian optimization of functio…
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Poompol Buathong, David Ginsbourger, Tipaluck Krityakierne
We focus on kernel methods for set-valued inputs and their application to Bayesian set optimization, notably combinatorial optimization. We investigate two classes of set kernels t…