4 papers
A KKL Observer Perspective on Reservoir Computing
Anastasia Bizyaeva, Fernando Castaños, Jaime A. Moreno
Reservoir computing (RC) is a machine learning technique for data-driven modeling of dynamics for forecasting and control, primarily studied in computer science and physics literat…
On Dominant Manifolds in Reservoir Computing Networks
Noa Kaplan, Alberto Padoan, Anastasia Bizyaeva
Understanding how training shapes the geometry of recurrent network dynamics is a central problem in time-series modeling. We study the emergence of low-dimensional dominant manifo…
Fourier Weak SINDy: Spectral Test Function Selection for Robust Model Identification
Zhiheng Chen, Urban Fasel, Anastasia Bizyaeva
We introduce Fourier Weak SINDy, a minimal noise-robust and interpretable derivative-free equation learning method that combines weak-form sparse equation learning with spectral de…
From Vision to Decision: Neuromorphic Control for Autonomous Navigation and Tracking
Chuwei Wang, Eduardo Sebastián, Amanda Prorok +1
Robotic navigation has historically struggled to reconcile reactive, sensor-based control with the decisive capabilities of model-based planners. This duality becomes critical when…