2 citations · 2 across the 6 of their papers we have counts for
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cs.LG2025
Position: Biology is the Challenge Physics-Informed ML Needs to Evolve
Julien Martinelli
Physics-Informed Machine Learning (PIML) has successfully integrated mechanistic understanding into machine learning, particularly in domains governed by well-known physical laws.…
cs.LG2023
Learning Relevant Contextual Variables Within Bayesian Optimization
Julien Martinelli, Ayush Bharti, Armi Tiihonen +5
Contextual Bayesian Optimization (CBO) efficiently optimizes black-box functions with respect to design variables, while simultaneously integrating contextual information regarding…
cs.LG2022★ 2 cited
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
Petrus Mikkola, Julien Martinelli, Louis Filstroff +1
Bayesian optimization (BO) is a powerful framework for optimizing black-box, expensive-to-evaluate functions. Over the past decade, many algorithms have been proposed to integrate…