117 citations · 398 across the 51 of their papers we have counts for
6 papers · 1 filter
Diffusion Maps Kalman Filter for a Class of Systems with Gradient Flows
Tal Shnitzer, Ronen Talmon, Jean-Jacques Slotine
In this paper, we propose a non-parametric method for state estimation of high-dimensional nonlinear stochastic dynamical systems, which evolve according to gradient flows with iso…
DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic Sampling
Gautam Pai, Ronen Talmon, Alex Bronstein +1
This paper explores a fully unsupervised deep learning approach for computing distance-preserving maps that generate low-dimensional embeddings for a certain class of manifolds. We…
Data-Driven Tree Transforms and Metrics
Gal Mishne, Ronen Talmon, Israel Cohen +2
We consider the analysis of high dimensional data given in the form of a matrix with columns consisting of observations and rows consisting of features. Often the data is such that…
Mahalanonbis Distance Informed by Clustering
Almog Lahav, Ronen Talmon, Yuval Kluger
A fundamental question in data analysis, machine learning and signal processing is how to compare between data points. The choice of the distance metric is specifically challenging…
An Emergent Space for Distributed Data with Hidden Internal Order through Manifold Learning
Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich +7
Manifold-learning techniques are routinely used in mining complex spatiotemporal data to extract useful, parsimonious data representations/parametrizations; these are, in turn, use…
Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment
Ori Katz, Ronen Talmon, Yu-Lun Lo +1
The problem of information fusion from multiple data-sets acquired by multimodal sensors has drawn significant research attention over the years. In this paper, we focus on a parti…