Gal Elidan - RankMe

86 papers A* 7A 19B 4Misc 2Journal 39Unranked 14

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Do LLMs have Consistent Values? ICLR Naama Rozen, Liat Bezalel, Gal Elidan, Amir Globerson, Ella Daniel
2024	J	`jnl`	Do LLMs have Consistent Values? CoRR Naama Rozen, Gal Elidan, Amir Globerson, Ella Daniel
2024	A*	`conf`	TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools. NeurIPS Avi Caciularu, Alon Jacovi, Eyal Ben-David, Sasha Goldshtein, Tal Schuster, Jonathan Herzig, Gal Elidan, Amir Globerson
2024	J	`jnl`	TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools. CoRR Avi Caciularu, Alon Jacovi, Eyal Ben-David, Sasha Goldshtein, Tal Schuster, Jonathan Herzig, Gal Elidan, Amir Globerson
2024	J	`jnl`	Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulos, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim
2023	—	`conf`	Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment. ACL (2) Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson
2023	J	`jnl`	Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment. CoRR Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson
2023	—	`conf`	Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. ACL (1) Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor
2023	J	`jnl`	Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. CoRR Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor
2022	J	`jnl`	Active Learning with Label Comparisons. CoRR Gal Yona, Shay Moran, Gal Elidan, Amir Globerson
2022	A	`conf`	Active learning with label comparisons. UAI Gal Yona, Shay Moran, Gal Elidan, Amir Globerson
2022	J	`jnl`	Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning. CoRR Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan
2021	J	`jnl`	Convex Nonparanormal Regression. IEEE Signal Process. Lett. Yonatan Woodbridge, Gal Elidan, Ami Wiesel
2021	A*	`conf`	Explaining in Style: Training a GAN to explain a classifier in StyleSpace. ICCV Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
2021	J	`jnl`	Explaining in Style: Training a GAN to explain a classifier in StyleSpace. CoRR Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
2021	J	`jnl`	Flood forecasting with machine learning models in an operational framework. CoRR Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, Yossi Matias
2021	A*	`conf`	Net-DNF: Effective Deep Modeling of Tabular Data. ICLR Liran Katzir, Gal Elidan, Ran El-Yaniv
2021	B	`conf`	Solving Sokoban with Forward-Backward Reinforcement Learning. SOCS Yaron Shoham, Gal Elidan
2021	J	`jnl`	Solving Sokoban with forward-backward reinforcement learning. CoRR Yaron Shoham, Gal Elidan
2020	J	`jnl`	DNF-Net: A Neural Architecture for Tabular Data. CoRR Ami Abutbul, Gal Elidan, Liran Katzir, Ran El-Yaniv
2020	A*	`conf`	Dynamic Composition for Conversational Domain Exploration. WWW Idan Szpektor, Deborah Cohen, Gal Elidan, Michael Fink, Avinatan Hassidim, Orgad Keller, Sayali Kulkarni, Eran Ofek, Sagie Pudinsky, Asaf Revach, Shimi Salant, Yossi Matias
2020	J	`jnl`	HydroNets: Leveraging River Structure for Hydrologic Modeling. CoRR Zach Moshe, Asher Metzger, Gal Elidan, Frederik Kratzert, Sella Nevo, Ran El-Yaniv
2020	J	`jnl`	ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach. CoRR Sella Nevo, Gal Elidan, Avinatan Hassidim, Guy Shalev, Oren Gilon, Grey Nearing, Yossi Matias
2020	J	`jnl`	Normalizing Flow Regression. CoRR Yonatan Woodbridge, Gal Elidan, Ami Wiesel
2020	—	`conf`	Spectral Algorithm for Shared Low-rank Matrix Regressions. SAM Yotam Gigi, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias, Ami Wiesel
2019	A*	`conf`	Globally Optimal Learning for Structured Elliptical Losses. NeurIPS Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel
2019	J	`jnl`	Improved Detection of Adversarial Attacks via Penetration Distortion Maximization. CoRR Shai Rozenberg, Gal Elidan, Ran El-Yaniv
2019	A	`conf`	Learning Rules-First Classifiers. AISTATS Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan
2019	J	`jnl`	ML for Flood Forecasting at Scale. CoRR Sella Nevo, Vova Anisimov, Gal Elidan, Ran El-Yaniv, Pete Giencke, Yotam Gigi, Avinatan Hassidim, Zach Moshe, Mor Schlesinger, Guy Shalev, Ajai Tirumali, Ami Wiesel, Oleg Zlydenko, Yossi Matias
2019	—	`conf`	Robust multitask Elliptical Regression (ROMER). CAMSAP Nofar Noy, Yoav Wald, Gal Elidan, Ami Wiesel
2019	J	`jnl`	Spectral Algorithm for Low-rank Multitask Regression. CoRR Yotam Gigi, Ami Wiesel, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias
2019	J	`jnl`	Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many. CoRR Yotam Gigi, Gal Elidan, Avinatan Hassidim, Yossi Matias, Zach Moshe, Sella Nevo, Guy Shalev, Ami Wiesel
2019	J	`jnl`	Unmixing K-Gaussians With Application to Hyperspectral Imaging. IEEE Trans. Geosci. Remote. Sens. Yonatan Woodbridge, Uri Okun, Gal Elidan, Ami Wiesel
2018	J	`jnl`	Learning with Rules. CoRR Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan
2017	A*	`conf`	Logistic Markov Decision Processes. IJCAI Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu
2017	A	`ed.`	Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, UAI 2017, Sydney, Australia, August 11-15, 2017 UAI Gal Elidan, Kristian Kersting, Alexander Ihler
2017	A	`conf`	Scalable Learning of Non-Decomposable Objectives. AISTATS Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan
2017	J	`jnl`	Signal Detection in Complex Structured Para Normal Noise. IEEE Trans. Signal Process. Yonatan Woodbridge, Gal Elidan, Ami Wiesel
2016	A	`conf`	Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables. AISTATS Yaniv Tenzer, Gal Elidan
2016	A	`conf`	Improper Deep Kernels. AISTATS Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson
2016	J	`jnl`	Large-scale Learning With Global Non-Decomposable Objectives. CoRR Elad Eban, Mariano Schain, Ariel Gordon, Rif Saurous, Gal Elidan
2016	Misc	`conf`	Quaternion structured paranormal distributions. ACSSC Yonatan Woodbridge, Gal Elidan, Ami Wiesel
2016	Misc	`conf`	Signal detection in para complex normal noise. ICASSP Yonatan Woodbridge, Gal Elidan, Ami Wiesel
2014	A	`conf`	HELM: Highly Efficient Learning of Mixed copula networks. UAI Yaniv Tenzer, Gal Elidan
2013	A	`conf`	Dynamic Copula Networks for Modeling Real-valued Time Series. AISTATS Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan
2013	A	`conf`	Learning Max-Margin Tree Predictors. UAI Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
2013	J	`jnl`	Learning Max-Margin Tree Predictors. CoRR Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
2013	J	`jnl`	Learning the Dimensionality of Hidden Variables CoRR Gal Elidan, Nir Friedman
2013	A	`conf`	Speedy Model Selection (SMS) for Copula Models. UAI Yaniv Tenzer, Gal Elidan
2013	J	`jnl`	Speedy Model Selection (SMS) for Copula Models. CoRR Yaniv Tenzer, Gal Elidan
2012	J	`jnl`	"Ideal Parent" Structure Learning for Continuous Variable Networks CoRR Iftach Nachman, Gal Elidan, Nir Friedman
2012	B	`conf`	A Diverse Dirichlet Process Ensemble for Unsupervised Induction of Syntactic Categories. COLING Roi Reichart, Gal Elidan, Ari Rappoport
2012	J	`jnl`	Convex Point Estimation using Undirected Bayesian Transfer Hierarchies CoRR Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller
2012	A	`conf`	Copula Network Classifiers (CNCs). AISTATS Gal Elidan
2012	J	`jnl`	Inference-less Density Estimation using Copula Bayesian Networks CoRR Gal Elidan
2012	A	`conf`	Lightning-speed Structure Learning of Nonlinear Continuous Networks. AISTATS Gal Elidan
2012	—	`conf`	Nonparanormal Belief Propagation (NPNBP). NIPS Gal Elidan, Cobi Cario
2012	J	`jnl`	Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing. CoRR Gal Elidan, Ian McGraw, Daphne Koller
2012	J	`jnl`	The Information Bottleneck EM Algorithm CoRR Gal Elidan, Nir Friedman
2011	A	`conf`	Bagged Structure Learning of Bayesian Network. AISTATS Gal Elidan
2010	—	`conf`	Copula Bayesian Networks. NIPS Gal Elidan
2010	J	`jnl`	FastInf: An Efficient Approximate Inference Library. J. Mach. Learn. Res. Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan
2010	A	`conf`	Inference-less Density Estimation using Copula Bayesian Networks. UAI Gal Elidan
2009	J	`jnl`	Shape-Based Object Localization for Descriptive Classification. Int. J. Comput. Vis. Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller
2008	A	`conf`	Convex Point Estimation using Undirected Bayesian Transfer Hierarchies. UAI Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller
2008	—	`conf`	Learning Bounded Treewidth Bayesian Networks. NIPS Gal Elidan, Stephen Gould
2008	J	`jnl`	Max-margin Classification of Data with Absent Features. J. Mach. Learn. Res. Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
2008	J	`jnl`	Multi-Class Segmentation with Relative Location Prior. Int. J. Comput. Vis. Stephen Gould, Jim Rodgers, David Cohen, Gal Elidan, Daphne Koller
2008	—	`conf`	Shape-Based Object Localization for Descriptive Classification. NIPS Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller
2007	J	`jnl`	"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks. J. Mach. Learn. Res. Gal Elidan, Iftach Nachman, Nir Friedman
2006	—	`conf`	Learning Object Shape: From Drawings to Images. CVPR (2) Gal Elidan, Geremy Heitz, Daphne Koller
2006	—	`conf`	Max-margin classification of incomplete data. NIPS Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
2006	A	`conf`	Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing. UAI Gal Elidan, Ian McGraw, Daphne Koller
2006	J	`jnl`	Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach. J. Comput. Biol. Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
2006	—	`conf`	Using Combinatorial Optimization within Max-Product Belief Propagation. NIPS John C. Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller
2005	J	`jnl`	CIS: compound importance sampling method for protein-DNA binding site p-value estimation. Bioinform. Yoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman
2005	J	`jnl`	Learning Hidden Variable Networks: The Information Bottleneck Approach. J. Mach. Learn. Res. Gal Elidan, Nir Friedman
2005	B	`conf`	Towards an Integrated Protein-Protein Interaction Network. RECOMB Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
2004	A	`conf`	"Ideal Parent" Structure Learning for Continuous Variable Networks. UAI Iftach Nachman, Gal Elidan, Nir Friedman
2004	—	`—`	Learning hidden variables in probabilistic graphical models (למידת משתנים חבויים במודלים גרפיים הסתברותיים.). Gal Elidan
2003	B	`conf`	Modeling dependencies in protein-DNA binding sites. RECOMB Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan
2003	A	`conf`	The Information Bottleneck EM Algorithm. UAI Gal Elidan, Nir Friedman
2002	—	`conf`	Data Perturbation for Escaping Local Maxima in Learning. AAAI/IAAI Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans
2001	—	`conf`	Inferring subnetworks from perturbed expression profiles. ISMB (Supplement of Bioinformatics) Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman
2001	A	`conf`	Learning the Dimensionality of Hidden Variables. UAI Gal Elidan, Nir Friedman
2000	—	`conf`	Discovering Hidden Variables: A Structure-Based Approach. NIPS Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller