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ML Optimization for Concentrated Solar Power Plants

We use Bayesian Optimization to improve dry cooling systems for concentrated solar power plants, making them more cost-competitive.

Robust and Provably Monotonic Networks

We develop a novel neural architecture with an exact bound on its Lipschitz constant. The model can be made monotonic in any subset of its features. This inductive bias is especially important for fairness and interpretability considerations.

Controlling Classifier Bias with Moment Decomposition: A Method to Enhance Searches for Resonances

Moment Decorrelation (MoDe) is a tool designed to ensure that a model's output remains uncorrelated with certain parameters, commonly termed as protected attributes in fairness contexts. Beyond mere decorrelation, MoDe can even shape the output of a model to adopt linear or quadratic relationships with any input/protected attribute.