Yaniv Gurwicz

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 18

Top Topics

Causal Discovery

Bayesian Network Structure Learning

Structure Learning

Top Venues

Publications

Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. CoRR (2023)
Raanan Y. Rohekar, Yaniv Gurwicz, Shami Nisimov
Causal Interpretation of Self-Attention in Pre-Trained Transformers. NeurIPS (2023)
Raanan Y. Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik
From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders. ICML (2023)
Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. NeurIPS (2023)
Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik
From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders. CoRR (2023)
Julien Boussard, Chandni Nagda, Julia Kaltenborn, Charlotte Emilie Elektra Lange, Philippe Brouillard, Yaniv Gurwicz, Peer Nowack, David Rolnick
Towards Causal Representations of Climate Model Data. CoRR (2023)
Raanan Y. Rohekar, Yaniv Gurwicz, Shami Nisimov
Causal Interpretation of Self-Attention in Pre-Trained Transformers. CoRR (2023)
Shami Nisimov, Raanan Y. Rohekar, Yaniv Gurwicz, Guy Koren, Gal Novik
CLEAR: Causal Explanations from Attention in Neural Recommenders. CoRR (2022)
Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias. NeurIPS (2021)
Shami Nisimov, Yaniv Gurwicz, Raanan Rohekar, Gal Novik
Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper. CoRR (2021)
Raanan Y. Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias. CoRR (2021)
Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik
A Single Iterative Step for Anytime Causal Discovery. CoRR (2020)
Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections. CoRR (2019)
Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections. NeurIPS (2019)
Raanan Y. Yehezkel Rohekar, Shami Nisimov, Guy Koren, Yaniv Gurwicz, Gal Novik
Constructing Deep Neural Networks by Bayesian Network Structure Learning. CoRR (2018)
Raanan Y. Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz, Guy Koren, Gal Novik
Constructing Deep Neural Networks by Bayesian Network Structure Learning. NeurIPS (2018)
Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Guy Koren, Gal Novik
Bayesian Structure Learning by Recursive Bootstrap. NeurIPS (2018)
Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Guy Koren, Gal Novik
Bayesian Structure Learning by Recursive Bootstrap. CoRR (2018)
Yaniv Gurwicz, Raanan Yehezkel, Boaz Lachover
Multiclass object classification for real-time video surveillance systems. Pattern Recognit. Lett. 32 (6) (2011)
Yaniv Gurwicz, Boaz Lerner
Bayesian Class-Matched Multinet Classifier. SSPR/SPR (2006)
Yaniv Gurwicz, Boaz Lerner
Bayesian network classification using spline-approximated kernel density estimation. Pattern Recognit. Lett. 26 (11) (2005)
Yaniv Gurwicz, Boaz Lerner
Rapid Spline-based Kernel Density Estimation for Bayesian Networks. ICPR (3) (2004)