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Publications

2024

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2023

דלית קן־דרור פלדמן, קרין נהון, ורדית אבידן ורן גלעד בכרך

זיוף, זיוף עמוק (Deep-Fake), חוק הסרטונים ועקרון הפרשנות המצמצמת: מה הדין?

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

Graph Neural Networks Use Graphs When They Shouldn't

Hofit Wasserman-Rozen, Ran Gilad-Bachrach, Niva Elkin-Koren

Lost in Translation: The Limits of Explainability in AI

Hofit Wasserman Rozen, Niva Elkin-Koren, and Ran Gilad-Bachrach

The Case Against Explainability

Yonatan E. Brand, Dafna Schwartz, Eran Gazit, Aron S. Buchman, Ran Gilad-Bachrach and Jeffrey M. Hausdorff

Gait Detection from a Wrist-Worn Sensor Using Machine Learning Methods: A Daily Living Study in Older Adults and People with Parkinson’s Disease

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

Graph Trees with Attention

Nimrod Harel, Ran Gilad-Bachrach, Uri Obolski

Inherent Inconsistencies of Feature Importance

Pierre Laforgue, Giulia Clerici, Nicol`o Cesa-Bianchi, Ran Gilad-Bachrach

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits

Christopher Pyles, Francois van Schalkwyk, Gerard J. Gorman, Marijan Beg, Lee Stott, Nir Levy and Ran Gilad-Bachrach

PyBryt: auto-assessment and auto-grading for computational thinking

Roy Hirsch, Ran Gilad-Bachrach

Trees with Attention for Set Prediction Tasks

Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach

Marginal Contribution Feature Importance-an Axiomatic Approach for Explaining Data

Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon

Algorithmic copywriting: automated generation of health-related advertisements to improve their performance

2021

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2022

דלית קן־דרור פלדמן, קרין נהון, ורדית אבידן ורן גלעד בכרך

זיוף, זיוף עמוק (Deep-Fake), חוק הסרטונים ועקרון הפרשנות המצמצמת: מה הדין?

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

Graph Neural Networks Use Graphs When They Shouldn't

Hofit Wasserman-Rozen, Ran Gilad-Bachrach, Niva Elkin-Koren

Lost in Translation: The Limits of Explainability in AI

Hofit Wasserman Rozen, Niva Elkin-Koren, and Ran Gilad-Bachrach

The Case Against Explainability

Yonatan E. Brand, Dafna Schwartz, Eran Gazit, Aron S. Buchman, Ran Gilad-Bachrach and Jeffrey M. Hausdorff

Gait Detection from a Wrist-Worn Sensor Using Machine Learning Methods: A Daily Living Study in Older Adults and People with Parkinson’s Disease

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

Graph Trees with Attention

Nimrod Harel, Ran Gilad-Bachrach, Uri Obolski

Inherent Inconsistencies of Feature Importance

Pierre Laforgue, Giulia Clerici, Nicol`o Cesa-Bianchi, Ran Gilad-Bachrach

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits

Christopher Pyles, Francois van Schalkwyk, Gerard J. Gorman, Marijan Beg, Lee Stott, Nir Levy and Ran Gilad-Bachrach

PyBryt: auto-assessment and auto-grading for computational thinking

Roy Hirsch, Ran Gilad-Bachrach

Trees with Attention for Set Prediction Tasks

Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach

Marginal Contribution Feature Importance-an Axiomatic Approach for Explaining Data

Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon

Algorithmic copywriting: automated generation of health-related advertisements to improve their performance

2020

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2019

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2018

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2017

דלית קן־דרור פלדמן, קרין נהון, ורדית אבידן ורן גלעד בכרך

זיוף, זיוף עמוק (Deep-Fake), חוק הסרטונים ועקרון הפרשנות המצמצמת: מה הדין?

המשפט

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

Graph Neural Networks Use Graphs When They Shouldn't

arXiv:2309.04332

Hofit Wasserman-Rozen, Ran Gilad-Bachrach, Niva Elkin-Koren

Lost in Translation: The Limits of Explainability in AI

SSRN 4531323

Hofit Wasserman Rozen, Niva Elkin-Koren, and Ran Gilad-Bachrach

The Case Against Explainability

arXiv:2305.12167

Yonatan E. Brand, Dafna Schwartz, Eran Gazit, Aron S. Buchman, Ran Gilad-Bachrach and Jeffrey M. Hausdorff

Gait Detection from a Wrist-Worn Sensor Using Machine Learning Methods: A Daily Living Study in Older Adults and People with Parkinson’s Disease

Sensors

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

Graph Trees with Attention

arXiv:2207.02760

Nimrod Harel, Ran Gilad-Bachrach, Uri Obolski

Inherent Inconsistencies of Feature Importance

arXiv:2206.08204

Pierre Laforgue, Giulia Clerici, Nicol`o Cesa-Bianchi, Ran Gilad-Bachrach

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits

The 25th International Conference on
Artificial Intelligence and Statistics (AIStats)

Christopher Pyles, Francois van Schalkwyk, Gerard J. Gorman, Marijan Beg, Lee Stott, Nir Levy and Ran Gilad-Bachrach

PyBryt: auto-assessment and auto-grading for computational thinking

arXiv:2112.02144, 2021

Roy Hirsch, Ran Gilad-Bachrach

Trees with Attention for Set Prediction Tasks

International Conference on Machine Learning, 4250-4261

Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach

Marginal Contribution Feature Importance-an Axiomatic Approach for Explaining Data

International Conference on Machine Learning, 1324-1335

Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon

Algorithmic copywriting: automated generation of health-related advertisements to improve their performance

Information Retrieval Journal 24 (3), 205-239

2016

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2015

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2014

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2013

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2012

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2011

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1997-2010

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