2.2k citations · 5.9k across the 41 of their papers we have counts for
6 papers · 1 filter
Accurate Hydrologic Modeling Using Less Information
Guy Shalev, Ran El-Yaniv, Daniel Klotz +3
Joint models are a common and important tool in the intersection of machine learning and the physical sciences, particularly in contexts where real-world measurements are scarce. R…
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks
Shai Rozenberg, Gal Elidan, Ran El-Yaniv
This paper is concerned with the defense of deep models against adversarial attacks. Inspired by the certificate defense approach, we propose a maximal adversarial distortion (MAD)…
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships
Gal Sadeh Kenigsfield, Ran El-Yaniv
One of the most difficult tasks in scene understanding is recognizing interactions between objects in an image. This task is often called visual relationship detection (VRD). We co…
Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
Yair Feldman, Ran El-Yaniv
This paper is concerned with the task of multi-hop open-domain Question Answering (QA). This task is particularly challenging since it requires the simultaneous performance of text…
ML for Flood Forecasting at Scale
Sella Nevo, Vova Anisimov, Gal Elidan +11
Effective riverine flood forecasting at scale is hindered by a multitude of factors, most notably the need to rely on human calibration in current methodology, the limited amount o…
SelectiveNet: A Deep Neural Network with an Integrated Reject Option
Yonatan Geifman, Ran El-Yaniv
We consider the problem of selective prediction (also known as reject option) in deep neural networks, and introduce SelectiveNet, a deep neural architecture with an integrated rej…