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2020 – today
- 2024
[j8]Yakov Miron
, Florian Drews, Florian Faion, Dotan Di Castro, Itzik Klein:
RCF-TP: Radar-Camera Fusion With Temporal Priors for 3D Object Detection. IEEE Access 12: 127212-127223 (2024)- [c24]Ori Linial, Orly Avner, Dotan Di Castro:
CONFIDE: Contextual Finite Difference Modelling of PDEs. KDD 2024: 1839-1850 - [i32]Zhili Feng, Michal Moshkovitz, Dotan Di Castro, J. Zico Kolter:
An Axiomatic Approach to Model-Agnostic Concept Explanations. CoRR abs/2401.06890 (2024) - [i31]Nimrod Berman, Eitan Kosman, Dotan Di Castro, Omri Azencot:
Generative Modeling of Graphs via Joint Diffusion of Node and Edge Attributes. CoRR abs/2402.04046 (2024) - [i30]Nitsan Soffair, Dotan Di Castro, Orly Avner, Shie Mannor:
SQT - std Q-target. CoRR abs/2402.05950 (2024) - [i29]Shir Kozlovsky, Omkar Joglekar, Dotan Di Castro:
ISCUTE: Instance Segmentation of Cables Using Text Embedding. CoRR abs/2402.11996 (2024) - [i28]Mariia Pushkareva, Yuri Feldman, Csaba Domokos, Kilian Rambach, Dotan Di Castro:
Radar Spectra-Language Model for Automotive Scene Parsing. CoRR abs/2406.02158 (2024) - [i27]Omkar Joglekar, Tal Lancewicki, Shir Kozlovsky, Vladimir Tchuiev, Zohar Feldman, Dotan Di Castro:
Towards Natural Language-Driven Assembly Using Foundation Models. CoRR abs/2406.16093 (2024) - [i26]Moshe Kimhi, David Vainshtein, Chaim Baskin, Dotan Di Castro:
Robot Instance Segmentation with Few Annotations for Grasping. CoRR abs/2407.01302 (2024) - [i25]Yakov Miron, Dan Navon, Yuval Goldfracht, Dotan Di Castro, Itzik Klein:
Decentralized and Asymmetric Multi-Agent Learning in Construction Sites. CoRR abs/2409.10375 (2024) - 2023
- [j7]Yakov Miron, Yuval Goldfracht, Chana Ross, Dotan Di Castro, Itzik Klein:
Autonomous Dozer Sand Grading Under Localization Uncertainties. IEEE Robotics Autom. Lett. 8(1): 65-72 (2023) - [i24]Ori Linial, Orly Avner, Dotan Di Castro:
PDExplain: Contextual Modeling of PDEs in the Wild. CoRR abs/2303.15827 (2023) - [i23]Ben-ya Halevy, Yehudit Aperstein, Dotan Di Castro:
Offline Skill Graph (OSG): A Framework for Learning and Planning using Offline Reinforcement Learning Skills. CoRR abs/2306.13630 (2023) - 2022
- [c23]Yakov Miron, Yuval Goldfracht, Dotan Di Castro:
Towards Autonomous Grading in the Real World. ECCV Workshops (4) 2022: 107-117 - [c22]Eitan Kosman, Dotan Di Castro:
GraphVid: It only Takes a Few Nodes to Understand a Video. ECCV (35) 2022: 195-212 - [c21]Eitan Kosman, Joel Oren, Dotan Di Castro:
LSP: Acceleration of Graph Neural Networks via Locality Sensitive Pruning of Graphs. ICDM (Workshops) 2022: 690-697 - [c20]Shirli Di-Castro Shashua, Shie Mannor, Dotan Di Castro:
Analysis of Stochastic Processes through Replay Buffers. ICML 2022: 5039-5060 - [c19]Oren Spector, Vladimir Tchuiev, Dotan Di Castro:
InsertionNet 2.0: Minimal Contact Multi-Step Insertion Using Multimodal Multiview Sensory Input. ICRA 2022: 6330-6336 - [c18]Zohar Feldman, Hanna Ziesche, Ngo Anh Vien, Dotan Di Castro:
A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives. ICRA 2022: 6365-6371 - [c17]Vladimir Tchuiev, Yakov Miron, Dotan Di Castro:
DUQIM-Net: Probabilistic Object Hierarchy Representation for Multi-View Manipulation. IROS 2022: 10470-10477 - [c16]Yakov Miron, Chana Ross, Yuval Goldfracht, Chen Tessler, Dotan Di Castro:
Towards Autonomous Grading In The Real World. IROS 2022: 11940-11946 - [i22]Oren Spector, Vladimir Tchuiev, Dotan Di Castro:
InsertionNet 2.0: Minimal Contact Multi-Step Insertion Using Multimodal Multiview Sensory Input. CoRR abs/2203.01153 (2022) - [i21]Yakov Miron, Chana Ross, Yuval Goldfracht, Chen Tessler, Dotan Di Castro:
Towards Autonomous Grading In The Real World. CoRR abs/2206.06091 (2022) - [i20]Shirli Di-Castro Shashua, Shie Mannor, Dotan Di Castro:
Analysis of Stochastic Processes through Replay Buffers. CoRR abs/2206.12848 (2022) - [i19]Eitan Kosman, Dotan Di Castro:
GraphVid: It Only Takes a Few Nodes to Understand a Video. CoRR abs/2207.01375 (2022) - [i18]Vladimir Tchuiev, Yakov Miron, Dotan Di Castro:
DUQIM-Net: Probabilistic Object Hierarchy Representation for Multi-View Manipulation. CoRR abs/2207.09105 (2022) - [i17]Yakov Miron, Yuval Goldfracht, Chana Ross, Dotan Di Castro, Itzik Klein:
AG2U - Autonomous Grading Under Uncertainties. CoRR abs/2208.02595 (2022) - 2021
- [j6]Oren Spector, Dotan Di Castro:
InsertionNet - A Scalable Solution for Insertion. IEEE Robotics Autom. Lett. 6(3): 5509-5516 (2021) - [c15]Shirli Di-Castro Shashua, Dotan Di Castro, Shie Mannor:
Sim and Real: Better Together. NeurIPS 2021: 6868-6880 - [c14]Joel Oren, Chana Ross, Maksym Lefarov, Felix Richter, Ayal Taitler, Zohar Feldman, Dotan Di Castro, Christian Daniel:
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems. SOCS 2021: 97-105 - [i16]Joel Oren, Chana Ross, Maksym Lefarov, Felix Richter, Ayal Taitler, Zohar Feldman, Christian Daniel, Dotan Di Castro:
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems. CoRR abs/2104.01646 (2021) - [i15]Oren Spector, Dotan Di Castro:
InsertionNet - A Scalable Solution for Insertion. CoRR abs/2104.14223 (2021) - [i14]Eitan Kosman, Dotan Di Castro:
Vision-Guided Forecasting - Visual Context for Multi-Horizon Time Series Forecasting. CoRR abs/2107.12674 (2021) - [i13]Adam Botach, Yuri Feldman, Yakov Miron, Yoel Shapiro, Dotan Di Castro:
BIDCD - Bosch Industrial Depth Completion Dataset. CoRR abs/2108.04706 (2021) - [i12]Shirli Di-Castro Shashua, Dotan Di Castro, Shie Mannor:
Sim and Real: Better Together. CoRR abs/2110.00445 (2021) - [i11]Zohar Feldman, Hanna Ziesche, Ngo Anh Vien, Dotan Di Castro:
A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives. CoRR abs/2111.01510 (2021) - [i10]Eitan Kosman, Joel Oren, Dotan Di Castro:
LSP : Acceleration and Regularization of Graph Neural Networks via Locality Sensitive Pruning of Graphs. CoRR abs/2111.05694 (2021) - [i9]Chana Ross, Yakov Miron, Yuval Goldfracht, Dotan Di Castro:
AGPNet - Autonomous Grading Policy Network. CoRR abs/2112.10877 (2021) - 2020
- [i8]Yuri Feldman, Yoel Shapiro, Dotan Di Castro:
Depth Completion with RGB Prior. CoRR abs/2008.07861 (2020)
2010 – 2019
- 2019
- [i7]Dotan Di Castro, Joel Oren, Shie Mannor:
Practical Risk Measures in Reinforcement Learning. CoRR abs/1908.08379 (2019) - 2018
- [c13]Dotan Di Castro, Iftah Gamzu, Irena Grabovitch-Zuyev, Liane Lewin-Eytan, Abhinav Pundir, Nil Ratan Sahoo, Michael Viderman:
Automated Extractions for Machine Generated Mail. WWW (Companion Volume) 2018: 655-662 - 2017
- [c12]Shahar Chen, Dotan Di Castro, Zohar S. Karnin, Liane Lewin-Eytan, Joseph (Seffi) Naor, Roy Schwartz:
Correlated Rounding of Multiple Uniform Matroids and Multi-Label Classification. ICALP 2017: 34:1-34:15 - 2016
- [j5]Aviv Tamar, Dotan Di Castro, Shie Mannor:
Learning the Variance of the Reward-To-Go. J. Mach. Learn. Res. 17: 13:1-13:36 (2016) - [c11]Noa Avigdor-Elgrabli, Mark Cwalinski, Dotan Di Castro, Iftah Gamzu, Irena Grabovitch-Zuyev, Liane Lewin-Eytan, Yoelle Maarek:
Structural Clustering of Machine-Generated Mail. CIKM 2016: 217-226 - [c10]Dotan Di Castro, Zohar Shay Karnin, Liane Lewin-Eytan, Yoelle Maarek:
You've got Mail, and Here is What you Could do With It!: Analyzing and Predicting Actions on Email Messages. WSDM 2016: 307-316 - [c9]Dotan Di Castro, Liane Lewin-Eytan, Yoelle Maarek, Ran Wolff, Eyal Zohar:
Enforcing k-anonymity in Web Mail Auditing. WSDM 2016: 327-336 - [i6]Yahel David, Dotan Di Castro, Zohar S. Karnin:
One-Shot Session Recommendation Systems with Combinatorial Items. CoRR abs/1607.01381 (2016) - 2015
- [j4]Daniel Soudry, Dotan Di Castro, Asaf Gal, Avinoam Kolodny, Shahar Kvatinsky:
Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training. IEEE Trans. Neural Networks Learn. Syst. 26(10): 2408-2421 (2015) - [i5]Assaf Hallak, Dotan Di Castro, Shie Mannor:
Contextual Markov Decision Processes. CoRR abs/1502.02259 (2015) - 2013
- [c8]Aviv Tamar, Dotan Di Castro, Shie Mannor:
Temporal Difference Methods for the Variance of the Reward To Go. ICML (3) 2013: 495-503 - [c7]Assaf Hallak, Dotan Di Castro, Shie Mannor:
Model selection in markovian processes. KDD 2013: 374-382 - [i4]Aviv Tamar, Dotan Di Castro, Shie Mannor:
Policy Evaluation with Variance Related Risk Criteria in Markov Decision Processes. CoRR abs/1301.0104 (2013) - 2012
- [j3]Aviv Tamar, Dotan Di Castro, Ron Meir:
Integrating a Partial Model into Model Free Reinforcement Learning. J. Mach. Learn. Res. 13: 1927-1966 (2012) - [c6]Dotan Di Castro, Aviv Tamar, Shie Mannor:
Policy Gradients with Variance Related Risk Criteria. ICML 2012 - 2011
- [c5]Aviv Tamar, Dotan Di Castro, Ron Meir:
Integrating Partial Model Knowledge in Model Free RL Algorithms. ICML 2011: 305-312 - [i3]Dotan Di Castro, Claudio Gentile, Shie Mannor:
Bandits with an Edge. CoRR abs/1109.2296 (2011) - 2010
- [j2]Dotan Di Castro, Ron Meir:
A Convergent Online Single Time Scale Actor Critic Algorithm. J. Mach. Learn. Res. 11: 367-410 (2010) - [c4]Dotan Di Castro, Shie Mannor:
Tutor learning using linear constraints in approximate dynamic programming. Allerton 2010: 1384-1390 - [c3]Dotan Di Castro, Shie Mannor:
Adaptive bases for Q-learning. CDC 2010: 4587-4593 - [c2]Dotan Di Castro, Shie Mannor:
Adaptive Bases for Reinforcement Learning. ECML/PKDD (1) 2010: 312-327 - [i2]Dotan Di Castro, Shie Mannor:
Adaptive Bases for Reinforcement Learning. CoRR abs/1005.0125 (2010)
2000 – 2009
- 2009
- [j1]Dotan Di Castro, Ron Meir, Irad Yavneh:
Delays and Oscillations in Networks of Spiking Neurons: A Two-Timescale Analysis. Neural Comput. 21(4): 1100-1124 (2009) - [i1]Dotan Di Castro, Ronny Meir:
A Convergent Online Single Time Scale Actor Critic Algorithm. CoRR abs/0909.2934 (2009) - 2008
- [c1]Dotan Di Castro, Dmitry Volkinshtein, Ron Meir:
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation. NIPS 2008: 385-392
Coauthor Index
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last updated on 2024-10-15 00:23 CEST by the dblp team
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