Brian de Silva

According to our database, Brian de Silva authored at least 11 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator.

Shaowu Pan, Eurika Kaiser, Brian M. de Silva, J. Nathan Kutz, Steven L. Brunton

J. Open Source Softw., April, 2024

2023

Semantic matching for text classification with complex class descriptions.

Brian de Silva, Kuan-Wen Huang, Gwang Lee, Karen Hovsepian, Yan Xu, Mingwei Shen

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Deeptime: a Python library for machine learning dynamical models from time series data.

Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé

Mach. Learn. Sci. Technol., 2022

PySINDy: A comprehensive Python package for robust sparse system identification.

Alan A. Kaptanoglu, Brian de Silva, Urban Fasel, Kadierdan Kaheman, Andy Goldschmidt, Jared Callaham, Charles B. Delahunt, Zachary Nicolaou, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton

J. Open Source Softw., 2022

2021

PySensors: A Python package for sparse sensor placement.

Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton

J. Open Source Softw., 2021

PySINDy: A comprehensive Python package for robust sparse system identification.

Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel, Kadierdan Kaheman, Jared L. Callaham, Charles B. Delahunt, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton

CoRR, 2021

2020

PySINDy: A Python package for the sparse identification of nonlinear dynamical systems from data.

Brian de Silva, Kathleen P. Champion, Markus Quade, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton

J. Open Source Softw., 2020

Discovery of Physics From Data: Universal Laws and Discrepancies.

Brian de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz

Frontiers Artif. Intell., 2020

Physics-informed machine learning for sensor fault detection with flight test data.

Brian M. de Silva, Jared Callaham, Jonathan Jonker, Nicholas Goebel, Jennifer Klemisch, Darren McDonald, Nathan Hicks, J. Nathan Kutz, Steven L. Brunton, Aleksandr Y. Aravkin

CoRR, 2020

2019

Discovery of Physics from Data: Universal Laws and Discrepancy Models.

Brian de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz

CoRR, 2019

2014

Prediction of Foreign Box Office Revenues Based on Wikipedia Page Activity.

Brian de Silva, Ryan Compton

CoRR, 2014