From the 1 of 5 linked papers with an AI index.
5 papers
Origins and mitigation of double descent in reduced order modeling
Andrei A. Klishin, J. Nathan Kutz, Krithika Manohar
The paper investigates why double descent errors occur in reduced‑order models and proposes a data‑noise averaging framework to predict and mitigate these instabilities, demonstrat…
From STLS to Projection-based Dictionary Selection in Sparse Regression for System Identification
Hangjun Cho, Fabio V. G. Amaral, Andrei A. Klishin +2
In this work, we revisit dictionary-based sparse regression, in particular, Sequential Threshold Least Squares (STLS), and propose a score-guided library selection to provide pract…
PySensors 2.0: A Python Package for Sparse Sensor Placement
Niharika Karnik, Yash Bhangale, Mohammad G. Abdo +6
PySensors is a Python package for selecting and placing a sparse set of sensors for reconstruction and classification tasks. In this major update to PySensors, we introduce spatial…
Data-Induced Interactions of Sparse Sensors Using Statistical Physics
Andrei A. Klishin, J. Nathan Kutz, Krithika Manohar
Large-dimensional empirical data in science and engineering frequently have a low-rank structure and can be represented as a combination of just a few eigenmodes. Because of this s…
Statistical Mechanics of Dynamical System Identification
Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz +1
Recovering dynamical equations from observed noisy data is the central challenge of system identification. We develop a statistical mechanics approach to analyze sparse equation di…