| 2026 | SP | Mad-Dag: Protecting Blockchain Consensus From MEV. | Roi Bar Zur, Ittay Eyal, Aviv Tamar |
| 2025 | ICLR | EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. | Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang |
| 2025 | ICML | A Classification View on Meta Learning Bandits. | Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar |
| 2025 | ICRA | From Configuration-Space Clearance to Feature-Space Margin: Sample Complexity in Learning-Based Collision Detection. | Sapir Tubul, Aviv Tamar, Kiril Solovey, Oren Salzman |
| 2024 | ICLR | Entity-Centric Reinforcement Learning for Object Manipulation from Pixels. | Dan Haramati, Tal Daniel, Aviv Tamar |
| 2024 | ICLR | MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning. | Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar |
| 2024 | ICML | A Bayesian Approach to Online Planning. | Nir Greshler, David Ben-Eli, Carmel Rabinovitz, Gabi Guetta, Liran Gispan, Guy Zohar, Aviv Tamar |
| 2024 | ICML | Test-Time Regret Minimization in Meta Reinforcement Learning. | Mirco Mutti, Aviv Tamar |
| 2023 | CoRL | Fine-Tuning Generative Models as an Inference Method for Robotic Tasks. | Orr Krupnik, Elisei Shafer, Tom Jurgenson, Aviv Tamar |
| 2023 | CoRL | Hierarchical Planning for Rope Manipulation using Knot Theory and a Learned Inverse Model. | Matan Sudry, Tom Jurgenson, Aviv Tamar, Erez Karpas |
| 2023 | ICML | ContraBAR: Contrastive Bayes-Adaptive Deep RL. | Era Choshen, Aviv Tamar |
| 2023 | ICML | Learning Control by Iterative Inversion. | Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar |
| 2023 | ICML | TGRL: An Algorithm for Teacher Guided Reinforcement Learning. | Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal |
| 2023 | ICRA | Online Tool Selection with Learned Grasp Prediction Models. | Khashayar Rohanimanesh, Jake Metzger, William Richards, Aviv Tamar |
| 2023 | NSDI | DOTE: Rethinking (Predictive) WAN Traffic Engineering. | Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch, Srikanth Kandula, Ishai Menache, Michael Schapira, Aviv Tamar |
| 2023 | SP | WeRLman: To Tackle Whale (Transactions), Go Deep (RL). | Roi Bar Zur, Ameer Abu-Hanna, Ittay Eyal, Aviv Tamar |
| 2023 | SP | Deep Bribe: Predicting the Rise of Bribery in Blockchain Mining with Deep RL. | Roi Bar Zur, Danielle Dori, Sharon Vardi, Ittay Eyal, Aviv Tamar |
| 2022 | AAAI | Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability. | Aviv Tamar, Daniel Soudry, Ev Zisselman |
| 2022 | ICML | Unsupervised Image Representation Learning with Deep Latent Particles. | Tal Daniel, Aviv Tamar |
| 2022 | ICRA | Validate on Sim, Detect on Real - Model Selection for Domain Randomization. | Gal Leibovich, Guy Jacob, Shadi Endrawis, Gal Novik, Aviv Tamar |
| 2022 | SYSTOR | WeRLman: to tackle whale (transactions), go deep (RL). | Roi Bar Zur, Ameer Abu-Hanna, Ittay Eyal, Aviv Tamar |
| 2021 | CVPR | Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder. | Tal Daniel, Aviv Tamar |
| 2021 | ICRA | Efficient Self-Supervised Data Collection for Offline Robot Learning. | Shadi Endrawis, Gal Leibovich, Guy Jacob, Gal Novik, Aviv Tamar |
| 2021 | ICRA | Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization. | Carmel Rabinovitz, Niko A. Grupen, Aviv Tamar |
| 2020 | AFT | Efficient MDP Analysis for Selfish-Mining in Blockchains. | Roi Bar Zur, Ittay Eyal, Aviv Tamar |
| 2020 | CVPR | Deep Residual Flow for Out of Distribution Detection. | Ev Zisselman, Aviv Tamar |
| 2020 | HOTNETS | Online Safety Assurance for Learning-Augmented Systems. | Noga H. Rotman, Michael Schapira, Aviv Tamar |
| 2020 | ICML | Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning. | Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar |
| 2020 | ICML | Hallucinative Topological Memory for Zero-Shot Visual Planning. | Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar |
| 2020 | IJCAI | Constrained Policy Improvement for Efficient Reinforcement Learning. | Elad Sarafian, Aviv Tamar, Sarit Kraus |
| 2019 | CoRL | Multi-Agent Reinforcement Learning with Multi-Step Generative Models. | Orr Krupnik, Igor Mordatch, Aviv Tamar |
| 2019 | ICCV | Bayesian Relational Memory for Semantic Visual Navigation. | Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian |
| 2019 | ICML | Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN. | Dror Freirich, Tzahi Shimkin, Ron Meir, Aviv Tamar |
| 2019 | ICML | A Deep Reinforcement Learning Perspective on Internet Congestion Control. | Nathan Jay, Noga H. Rotman, Brighten Godfrey, Michael Schapira, Aviv Tamar |
| 2019 | ICRA | Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly. | Jianlan Luo, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, Alice M. Agogino, Aviv Tamar, Pieter Abbeel |
| 2019 | ICRA | Domain Randomization for Active Pose Estimation. | Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel |
| 2018 | ICLR | Model-Ensemble Trust-Region Policy Optimization. | Thanard Kurutach, Ignasi Clavera, Yan Duan, Aviv Tamar, Pieter Abbeel |
| 2018 | ICLR | Imitation Learning from Visual Data with Multiple Intentions. | Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore |
| 2018 | ICRA | Learning Robotic Assembly from CAD. | Garrett Thomas, Melissa Chien, Aviv Tamar, Juan Aparicio Ojea, Pieter Abbeel |
| 2017 | HOTNETS | Learning to Route. | Asaf Valadarsky, Michael Schapira, Dafna Shahaf, Aviv Tamar |
| 2017 | ICML | Constrained Policy Optimization. | Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel |
| 2017 | IJCAI | Value Iteration Networks. | Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel |
| 2017 | ICRA | Learning from the hindsight plan - Episodic MPC improvement. | Aviv Tamar, Garrett Thomas, Tianhao Zhang, Sergey Levine, Pieter Abbeel |
| 2016 | AAAI | Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis. | Assaf Hallak, Aviv Tamar, Rmi Munos, Shie Mannor |
| 2015 | AAAI | Optimizing the CVaR via Sampling. | Aviv Tamar, Yonatan Glassner, Shie Mannor |
| 2014 | ICML | Scaling Up Robust MDPs using Function Approximation. | Aviv Tamar, Shie Mannor, Huan Xu |
| 2013 | ICML | Temporal Difference Methods for the Variance of the Reward To Go. | Aviv Tamar, Dotan Di Castro, Shie Mannor |
| 2012 | ICML | Policy Gradients with Variance Related Risk Criteria. | Dotan Di Castro, Aviv Tamar, Shie Mannor |
| 2011 | ICML | Integrating Partial Model Knowledge in Model Free RL Algorithms. | Aviv Tamar, Dotan Di Castro, Ron Meir |