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2020 – today
- 2023
[c8]Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar:
Learning Control by Iterative Inversion. ICML 2023: 19228-19255- [c7]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: 39939-39950 - [i13]Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik:
From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders. CoRR abs/2306.00624 (2023) - 2022
- [c6]Gal Leibovich, Guy Jacob, Shadi Endrawis, Gal Novik, Aviv Tamar:
Validate on Sim, Detect on Real - Model Selection for Domain Randomization. ICRA 2022: 7528-7535 - [i12]Shami Nisimov, Raanan Y. Rohekar, Yaniv Gurwicz, Guy Koren, Gal Novik:
CLEAR: Causal Explanations from Attention in Neural Recommenders. CoRR abs/2210.10621 (2022) - [i11]Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar:
Learning Control by Iterative Inversion. CoRR abs/2211.01724 (2022) - [i10]Dan Elbaz, Gal Novik, Oren Salzman:
Wall Street Tree Search: Risk-Aware Planning for Offline Reinforcement Learning. CoRR abs/2211.04583 (2022) - 2021
- [c5]Shadi Endrawis, Gal Leibovich, Guy Jacob, Gal Novik, Aviv Tamar:
Efficient Self-Supervised Data Collection for Offline Robot Learning. ICRA 2021: 4650-4656 - [c4]Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik:
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias. NeurIPS 2021: 2454-2465 - [i9]Shadi Endrawis, Gal Leibovich, Guy Jacob, Gal Novik, Aviv Tamar:
Efficient Self-Supervised Data Collection for Offline Robot Learning. CoRR abs/2105.04607 (2021) - [i8]Shami Nisimov, Yaniv Gurwicz, Raanan Y. Rohekar, Gal Novik:
Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper. CoRR abs/2107.05001 (2021) - [i7]Gal Leibovich, Guy Jacob, Shadi Endrawis, Gal Novik, Aviv Tamar:
Validate on Sim, Detect on Real - Model Selection for Domain Randomization. CoRR abs/2111.00765 (2021) - [i6]Raanan Y. Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik:
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias. CoRR abs/2111.04095 (2021) - 2020
- [i5]Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik:
A Single Iterative Step for Anytime Causal Discovery. CoRR abs/2012.07513 (2020)
2010 – 2019
- 2019
- [c3]Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik:
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections. NeurIPS 2019: 4246-4256 - [i4]Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik:
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections. CoRR abs/1905.13195 (2019) - [i3]Neta Zmora, Guy Jacob, Lev Zlotnik, Bar Elharar, Gal Novik:
Neural Network Distiller: A Python Package For DNN Compression Research. CoRR abs/1910.12232 (2019) - 2018
- [c2]Raanan Y. Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz, Guy Koren, Gal Novik:
Constructing Deep Neural Networks by Bayesian Network Structure Learning. NeurIPS 2018: 3051-3062 - [c1]Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Guy Koren, Gal Novik:
Bayesian Structure Learning by Recursive Bootstrap. NeurIPS 2018: 10546-10556 - [i2]Raanan Y. Yehezkel Rohekar, Shami Nisimov, Guy Koren, Yaniv Gurwicz, Gal Novik:
Constructing Deep Neural Networks by Bayesian Network Structure Learning. CoRR abs/1806.09141 (2018) - [i1]Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Guy Koren, Gal Novik:
Bayesian Structure Learning by Recursive Bootstrap. CoRR abs/1809.04828 (2018)
Coauthor Index
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