Bayesian Structure Learning by Recursive Bootstrap. - Raanan Y. Rohekar; Yaniv Gurwicz; Shami Nisimov; Guy Koren; Gal Novik (NeurIPS, 2018)

Constructing Deep Neural Networks by Bayesian Network Structure Learning. - Raanan Y. Rohekar; Shami Nisimov; Yaniv Gurwicz; Guy Koren; Gal Novik (NeurIPS, 2018)

Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections. - Raanan Y. Rohekar; Yaniv Gurwicz; Shami Nisimov; Gal Novik (NeurIPS, 2019)

A Single Iterative Step for Anytime Causal Discovery. - Raanan Y. Rohekar; Yaniv Gurwicz; Shami Nisimov; Gal Novik (CoRR, 2020)

Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias. - Raanan Y. Rohekar; Shami Nisimov; Yaniv Gurwicz; Gal Novik (NeurIPS, 2021)

Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper. - Shami Nisimov; Yaniv Gurwicz; Raanan Y. Rohekar; Gal Novik (CoRR, 2021)

CLEAR: Causal Explanations from Attention in Neural Recommenders. - Shami Nisimov; Raanan Y. Rohekar; Yaniv Gurwicz; Guy Koren; Gal Novik (CoRR, 2022)

From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders. - Raanan Y. Rohekar; Shami Nisimov; Yaniv Gurwicz; Gal Novik (ICML, 2023)

Causal Interpretation of Self-Attention in Pre-Trained Transformers. - Raanan Y. Rohekar; Yaniv Gurwicz; Shami Nisimov (NeurIPS, 2023)