6 citations · 19 across the 12 of their papers we have counts for
4 papers · 1 filter
Interpretable Transformation and Analysis of Timelines through Learning via Surprisability
Osnat Mokryn, Teddy Lazebnik, Hagit Ben Shoshan
The analysis of high-dimensional timeline data and the identification of outliers and anomalies is critical across diverse domains, including sensor readings, biological and medica…
Tighten The Lasso: A Convex Hull Volume-based Anomaly Detection Method
Uri Itai, Asael Bar Ilan, Teddy Lazebnik
Detecting out-of-distribution (OOD) data is a critical task for maintaining model reliability and robustness. In this study, we propose a novel anomaly detection algorithm that lev…
An Empirically-parametrized Spatio-Temporal Extended-SIR Model for Combined Dilution and Vaccination Mitigation for Rabies Outbreaks in Wild Jackals
Teddy Lazebnik, Yehuda Samuel, Jonathan Tichon +4
The transmission of zoonotic diseases between animals and humans poses an increasing threat. Rabies is a prominent example with various instances globally, facilitated by a surplus…
Data Augmentation for Deep Learning Regression Tasks by Machine Learning Models
Assaf Shmuel, Oren Glickman, Teddy Lazebnik
Deep learning (DL) models have gained prominence in domains such as computer vision and natural language processing but remain underutilized for regression tasks involving tabular…