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Raymundo Arroyave

3 accepted papers

2026

Probability of Matching for Batch Multi-Objective Bayesian Optimization

ICML 2026poster

In batch multi-objective Bayesian optimization (MOBO), it is often desirable to identify the whole Pareto optimal set, especially when considering the complicated interplay between different design criteria and constraints. This poses unique challenges in acquiring batches of both high quality and d…

Cited by 0SourceScholar
2024

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation

NeurIPS 2024poster

We consider the problem of crystal materials generation using language models (LMs). A key step is to convert 3D crystal structures into 1D sequences to be processed by LMs. Prior studies used the crystallographic information framework (CIF) file stream, which fails to ensure SE(3) and periodic inva…

Cited by 4SourcePDFScholar
2021

Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science

AAAI 2021technical

Automatic Feature Engineering (AFE) aims to extract useful knowledge for interpretable predictions given data for the machine learning tasks. Here, we develop AFE to extract dependency relationships that can be interpreted with functional formulas to discover physics meaning or new hypotheses for th…