117 citations · 398 across the 51 of their papers we have counts for
7 papers · 1 filter
No equations, no parameters, no variables: data, and the reconstruction of normal forms by learning informed observation geometries
Or Yair, Ronen Talmon, Ronald R. Coifman +1
The discovery of physical laws consistent with empirical observations lies at the heart of (applied) science and engineering. These laws typically take the form of nonlinear differ…
Multimodal Latent Variable Analysis
Vardan Papyan, Ronen Talmon
Consider a set of multiple, multimodal sensors capturing a complex system or a physical phenomenon of interest. Our primary goal is to distinguish the underlying sources of variabi…
Semi-Supervised Source Localization on Multiple-Manifolds with Distributed Microphones
Bracha Laufer-Goldshtein, Ronen Talmon, Sharon Gannot
The problem of source localization with ad hoc microphone networks in noisy and reverberant enclosures, given a training set of prerecorded measurements, is addressed in this paper…
Local Canonical Correlation Analysis for Nonlinear Common Variables Discovery
Or Yair, Ronen Talmon
In this paper, we address the problem of hidden common variables discovery from multimodal data sets of nonlinear high-dimensional observations. We present a metric based on local…
Manifold Learning with Contracting Observers for Data-driven Time-series Analysis
Tal Shnitzer, Ronen Talmon, Jean-Jacques Slotine
Analyzing signals arising from dynamical systems typically requires many modeling assumptions and parameter estimation. In high dimensions, this modeling is particularly difficult…
Kernel-based Sensor Fusion with Application to Audio-Visual Voice Activity Detection
David Dov, Ronen Talmon, Israel Cohen
In this paper, we address the problem of multiple view data fusion in the presence of noise and interferences. Recent studies have approached this problem using kernel methods, by…