Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation. - Dotan Di Castro; Dmitry Volkinshtein; Ron Meir (NIPS, 2008)

Delays and Oscillations in Networks of Spiking Neurons: A Two-Timescale Analysis. - Dotan Di Castro; Ron Meir; Irad Yavneh (Neural Comput., 2009)

Tutor learning using linear constraints in approximate dynamic programming. - Dotan Di Castro; Shie Mannor (Allerton, 2010)

Adaptive bases for Q-learning. - Dotan Di Castro; Shie Mannor (CDC, 2010)

Adaptive Bases for Reinforcement Learning. - Dotan Di Castro; Shie Mannor (ECML/PKDD (1), 2010)

A Convergent Online Single Time Scale Actor Critic Algorithm. - Dotan Di Castro; Ron Meir (J. Mach. Learn. Res., 2010)

Integrating Partial Model Knowledge in Model Free RL Algorithms. - Aviv Tamar; Dotan Di Castro; Ron Meir (ICML, 2011)

Bandits with an Edge - Dotan Di Castro; Claudio Gentile; Shie Mannor (CoRR, 2011)

Policy Gradients with Variance Related Risk Criteria. - Dotan Di Castro; Aviv Tamar; Shie Mannor (ICML, 2012)

Integrating a Partial Model into Model Free Reinforcement Learning. - Aviv Tamar; Dotan Di Castro; Ron Meir (J. Mach. Learn. Res., 2012)

Temporal Difference Methods for the Variance of the Reward To Go. - Aviv Tamar; Dotan Di Castro; Shie Mannor (ICML (3), 2013)

Model selection in markovian processes. - Assaf Hallak; Dotan Di Castro; Shie Mannor (KDD, 2013)

Policy Evaluation with Variance Related Risk Criteria in Markov Decision Processes - Aviv Tamar; Dotan Di Castro; Shie Mannor (CoRR, 2013)

Contextual Markov Decision Processes. - Assaf Hallak; Dotan Di Castro; Shie Mannor (CoRR, 2015)

Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training. - Daniel Soudry; Dotan Di Castro; Asaf Gal; Avinoam Kolodny; Shahar Kvatinsky (IEEE Trans. Neural Networks Learn. Syst., 2015)

Structural Clustering of Machine-Generated Mail. - Noa Avigdor-Elgrabli; Mark Cwalinski; Dotan Di Castro; Iftah Gamzu; Irena Grabovitch-Zuyev; Liane Lewin-Eytan; Yoelle Maarek (CIKM, 2016)

You've got Mail, and Here is What you Could do With It!: Analyzing and Predicting Actions on Email Messages. - Dotan Di Castro; Zohar Shay Karnin; Liane Lewin-Eytan; Yoelle Maarek (WSDM, 2016)

Enforcing k-anonymity in Web Mail Auditing. - Dotan Di Castro; Liane Lewin-Eytan; Yoelle Maarek; Ran Wolff 003; Eyal Zohar (WSDM, 2016)

One-Shot Session Recommendation Systems with Combinatorial Items. - Yahel David; Dotan Di Castro; Zohar S. Karnin (CoRR, 2016)

Learning the Variance of the Reward-To-Go. - Aviv Tamar; Dotan Di Castro; Shie Mannor (J. Mach. Learn. Res., 2016)

Correlated Rounding of Multiple Uniform Matroids and Multi-Label Classification. - Shahar Chen; Dotan Di Castro; Zohar S. Karnin; Liane Lewin-Eytan; Joseph (Seffi) Naor; Roy Schwartz 002 (ICALP, 2017)

Automated Extractions for Machine Generated Mail. - Dotan Di Castro; Iftah Gamzu; Irena Grabovitch-Zuyev; Liane Lewin-Eytan; Abhinav Pundir; Nil Ratan Sahoo; Michael Viderman (WWW (Companion Volume), 2018)

Practical Risk Measures in Reinforcement Learning. - Dotan Di Castro; Joel Oren; Shie Mannor (CoRR, 2019)

Depth Completion with RGB Prior. - Yuri Feldman; Yoel Shapiro; Dotan Di Castro (CoRR, 2020)

Sim and Real: Better Together. - Shirli Di-Castro Shashua; Dotan Di Castro; Shie Mannor (NeurIPS, 2021)

SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems. - Joel Oren; Chana Ross; Maksym Lefarov; Felix Richter 001; Ayal Taitler; Zohar Feldman; Dotan Di Castro; Christian Daniel (SOCS, 2021)

Vision-Guided Forecasting - Visual Context for Multi-Horizon Time Series Forecasting. - Eitan Kosman; Dotan Di Castro (CoRR, 2021)

BIDCD - Bosch Industrial Depth Completion Dataset. - Adam Botach; Yuri Feldman; Yakov Miron; Yoel Shapiro; Dotan Di Castro (CoRR, 2021)

LSP : Acceleration and Regularization of Graph Neural Networks via Locality Sensitive Pruning of Graphs. - Eitan Kosman; Joel Oren; Dotan Di Castro (CoRR, 2021)

AGPNet - Autonomous Grading Policy Network. - Chana Ross; Yakov Miron; Yuval Goldfracht; Dotan Di Castro (CoRR, 2021)

InsertionNet - A Scalable Solution for Insertion. - Oren Spector; Dotan Di Castro (IEEE Robotics Autom. Lett., 2021)

GraphVid: It only Takes a Few Nodes to Understand a Video. - Eitan Kosman; Dotan Di Castro (ECCV (35), 2022)

Towards Autonomous Grading in the Real World. - Yakov Miron; Yuval Goldfracht; Dotan Di Castro (ECCV Workshops (4), 2022)

LSP: Acceleration of Graph Neural Networks via Locality Sensitive Pruning of Graphs. - Eitan Kosman; Joel Oren; Dotan Di Castro (ICDM (Workshops), 2022)

Analysis of Stochastic Processes through Replay Buffers. - Shirli Di-Castro Shashua; Shie Mannor; Dotan Di Castro (ICML, 2022)

A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives. - Zohar Feldman; Hanna Ziesche; Ngo Anh Vien; Dotan Di Castro (ICRA, 2022)

InsertionNet 2.0: Minimal Contact Multi-Step Insertion Using Multimodal Multiview Sensory Input. - Oren Spector; Vladimir Tchuiev; Dotan Di Castro (ICRA, 2022)

Towards Autonomous Grading In The Real World. - Yakov Miron; Chana Ross; Yuval Goldfracht; Chen Tessler; Dotan Di Castro (IROS, 2022)

DUQIM-Net: Probabilistic Object Hierarchy Representation for Multi-View Manipulation. - Vladimir Tchuiev; Yakov Miron; Dotan Di Castro (IROS, 2022)

AG2U - Autonomous Grading Under Uncertainties. - Yakov Miron; Yuval Goldfracht; Chana Ross; Dotan Di Castro; Itzik Klein (CoRR, 2022)

PDExplain: Contextual Modeling of PDEs in the Wild. - Ori Linial; Orly Avner; Dotan Di Castro (CoRR, 2023)

Offline Skill Graph (OSG): A Framework for Learning and Planning using Offline Reinforcement Learning Skills. - Ben-ya Halevy; Yehudit Aperstein; Dotan Di Castro (CoRR, 2023)

Autonomous Dozer Sand Grading Under Localization Uncertainties. - Yakov Miron; Yuval Goldfracht; Chana Ross; Dotan Di Castro; Itzik Klein (IEEE Robotics Autom. Lett., 2023)

CONFIDE: Contextual Finite Difference Modelling of PDEs. - Ori Linial; Orly Avner; Dotan Di Castro (KDD, 2024)

RCF-TP: Radar-Camera Fusion With Temporal Priors for 3D Object Detection. - Yakov Miron; Florian Drews; Florian Faion; Dotan Di Castro; Itzik Klein (IEEE Access, 2024)

An Axiomatic Approach to Model-Agnostic Concept Explanations. - Zhili Feng; Michal Moshkovitz; Dotan Di Castro; J. Zico Kolter (CoRR, 2024)

Generative Modeling of Graphs via Joint Diffusion of Node and Edge Attributes. - Nimrod Berman; Eitan Kosman; Dotan Di Castro; Omri Azencot (CoRR, 2024)

SQT - std Q-target. - Nitsan Soffair; Dotan Di Castro; Orly Avner; Shie Mannor (CoRR, 2024)

ISCUTE: Instance Segmentation of Cables Using Text Embedding. - Shir Kozlovsky; Omkar Joglekar; Dotan Di Castro (CoRR, 2024)

Radar Spectra-Language Model for Automotive Scene Parsing. - Mariia Pushkareva; Yuri Feldman; Csaba Domokos; Kilian Rambach; Dotan Di Castro (CoRR, 2024)

Towards Natural Language-Driven Assembly Using Foundation Models. - Omkar Joglekar; Tal Lancewicki; Shir Kozlovsky; Vladimir Tchuiev; Zohar Feldman; Dotan Di Castro (CoRR, 2024)

Decentralized and Asymmetric Multi-Agent Learning in Construction Sites. - Yakov Miron; Dan Navon; Yuval Goldfracht; Dotan Di Castro; Itzik Klein (CoRR, 2024)

Gradient-Free Neural Network Training on the Edge. - Dotan Di Castro; Omkar Joglekar; Shir Kozlovsky; Vladimir Tchuiev; Michal Moshkovitz (CoRR, 2024)

Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting. - Liran Nochumsohn; Michal Moshkovitz; Orly Avner; Dotan Di Castro; Omri Azencot (CoRR, 2024)

Adapter to facilitate Foundation Model Communication for DLO Instance Segmentation. - Omkar Joglekar; Shir Kozlovsky; Dotan Di Castro (UniReps, 2025)

Robot Instance Segmentation with Few Annotations for Grasping. - Moshe Kimhi; David Vainshtein; Chaim Baskin; Dotan Di Castro (WACV, 2025)

Reviving Life on the Edge: Joint Score-Based Graph Generation of Rich Edge Attributes. - Nimrod Berman; Eitan Kosman; Dotan Di Castro; Omri Azencot (Trans. Mach. Learn. Res., 2025)