24 citations · 107 across the 41 of their papers we have counts for
43 papers
Isotonic surrogate modeling for computer experiments with many input variables
Jaehoan Kim, Simon Mak
Virtual simulators are widely used for studying complex physical phenomena, from particle collisions to rocket propulsion. Such "computer experiments" can be highly time-intensive,…
Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts
Chao Peter Yang, Cynthia Rudin, Yue Jiang +2
Deep learning has transformed symbolic music generation by borrowing the training paradigms of large language models, with systems such as NotaGen now producing complete, stylistic…
Fast multitask Gaussian processes, with application to surrogate modeling of the quark-gluon plasma
Aleksei G. Sorokin, Pieterjan Robbe, Yen-Chun Liu +2
Gaussian processes (GPs) are broadly used for the surrogate modeling of computer experiments with reliable uncertainty quantification. Our motivating application comes from the stu…
A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis
Stephen Ni-Hahn, Weihan Xu, Jerry Yin +4
Schenkerian Analysis (SchA) is a uniquely expressive method of music analysis, combining elements of melody, harmony, counterpoint, and form to describe the hierarchical structure…
Targeted Variance Reduction: Robust Bayesian Optimization of Black-Box Simulators with Noise Parameters
John Joshua Miller, Simon Mak
The optimization of a black-box simulator over control parameters arises in a myriad of scientific applications. In such applications, the simulator often takes the fo…
BayesFLo: Bayesian fault localization of complex software systems
Yi Ji, Simon Mak, Ryan Lekivetz +1
Software testing is essential for the reliable development of complex software systems. A key step in software testing is fault localization, which uses test data to pinpoint failu…