Tamar, Aviv

51 publications

ICML 2025 A Classification View on Meta Learning Bandits Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar

NeurIPS 2025 Blindfolded Experts Generalize Better: Insights from Robotic Manipulation and Videogames Ev Zisselman, Mirco Mutti, Shelly Francis-Meretzki, Elisei Shafer, Aviv Tamar

ICLR 2025 EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang

NeurIPS 2025 Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies Zohar Rimon, Elisei Shafer, Tal Tepper, Efrat Shimron, Aviv Tamar

ICML 2024 A Bayesian Approach to Online Planning Nir Greshler, David Ben Eli, Carmel Rabinovitz, Gabi Guetta, Liran Gispan, Guy Zohar, Aviv Tamar

TMLR 2024 DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles Tal Daniel, Aviv Tamar

ICLR 2024 Entity-Centric Reinforcement Learning for Object Manipulation from Pixels Dan Haramati, Tal Daniel, Aviv Tamar

ICLR 2024 MAMBA: An Effective World Model Approach for Meta-Reinforcement Learning Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar

ICML 2024 Test-Time Regret Minimization in Meta Reinforcement Learning Mirco Mutti, Aviv Tamar

ICML 2023 ContraBAR: Contrastive Bayes-Adaptive Deep RL Era Choshen, Aviv Tamar

NeurIPSW 2023 Entity-Centric Reinforcement Learning for Object Manipulation from Pixels Dan Haramati, Tal Daniel, Aviv Tamar

NeurIPS 2023 Explore to Generalize in Zero-Shot RL Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar

NeurIPSW 2023 Explore to Generalize in Zero-Shot RL Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar

CoRL 2023 Fine-Tuning Generative Models as an Inference Method for Robotic Tasks Orr Krupnik, Elisei Shafer, Tom Jurgenson, Aviv Tamar

CoRL 2023 Hierarchical Planning for Rope Manipulation Using Knot Theory and a Learned Inverse Model Matan Sudry, Tom Jurgenson, Aviv Tamar, Erez Karpas

ICML 2023 Learning Control by Iterative Inversion Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar

ICML 2023 TGRL: An Algorithm for Teacher Guided Reinforcement Learning Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal

ICLRW 2023 TGRL: Teacher Guided Reinforcement Learning Algorithm for POMDPs Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal

NeurIPSW 2022 Learning Control by Iterative Inversion Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar

NeurIPS 2022 Meta Reinforcement Learning with Finite Training Tasks - A Density Estimation Approach Zohar Rimon, Aviv Tamar, Gilad Adler

AAAI 2022 Regularization Guarantees Generalization in Bayesian Reinforcement Learning Through Algorithmic Stability Aviv Tamar, Daniel Soudry, Ev Zisselman

ICML 2022 Unsupervised Image Representation Learning with Deep Latent Particles Tal Daniel, Aviv Tamar

NeurIPSW 2021 Deep Variational Semi-Supervised Novelty Detection Tal Daniel, Thanard Kurutach, Aviv Tamar

ICLRW 2021 Offline Meta Learning of Exploration Ron Dorfman, Idan Shenfeld, Aviv Tamar

NeurIPS 2021 Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies Ron Dorfman, Idan Shenfeld, Aviv Tamar

CVPR 2021 Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder Tal Daniel, Aviv Tamar

IJCAI 2020 Constrained Policy Improvement for Efficient Reinforcement Learning Elad Sarafian, Aviv Tamar, Sarit Kraus

ICML 2020 Hallucinative Topological Memory for Zero-Shot Visual Planning Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar

ICML 2020 Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar

ICML 2019 A Deep Reinforcement Learning Perspective on Internet Congestion Control Nathan Jay, Noga Rotman, Brighten Godfrey, Michael Schapira, Aviv Tamar

ICML 2019 Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN Dror Freirich, Tzahi Shimkin, Ron Meir, Aviv Tamar

CoRL 2019 Multi-Agent Reinforcement Learning with Multi-Step Generative Models Orr Krupnik, Igor Mordatch, Aviv Tamar

ICLR 2018 Imitation Learning from Visual Data with Multiple Intentions Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore

NeurIPS 2018 Learning Plannable Representations with Causal InfoGAN Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel

ICLR 2018 Model-Ensemble Trust-Region Policy Optimization Thanard Kurutach, Ignasi Clavera, Yan Duan, Aviv Tamar, Pieter Abbeel

ICML 2017 Constrained Policy Optimization Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel

NeurIPS 2017 Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, Igor Mordatch

NeurIPS 2017 Shallow Updates for Deep Reinforcement Learning Nir Levine, Tom Zahavy, Daniel J Mankowitz, Aviv Tamar, Shie Mannor

IJCAI 2017 Value Iteration Networks Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel

AAAI 2016 Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis Assaf Hallak, Aviv Tamar, Rémi Munos, Shie Mannor

JMLR 2016 Learning the Variance of the Reward-to-Go Aviv Tamar, Dotan Di Castro, Shie Mannor

NeurIPS 2016 Value Iteration Networks Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel

FnTML 2015 Bayesian Reinforcement Learning: A Survey Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar

AAAI 2015 Optimizing the CVaR via Sampling Aviv Tamar, Yonatan Glassner, Shie Mannor

NeurIPS 2015 Policy Gradient for Coherent Risk Measures Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

NeurIPS 2015 Risk-Sensitive and Robust Decision-Making: A CVaR Optimization Approach Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone

ICML 2014 Scaling up Robust MDPs Using Function Approximation Aviv Tamar, Shie Mannor, Huan Xu

ICML 2013 Temporal Difference Methods for the Variance of the Reward to Go Aviv Tamar, Dotan Di Castro, Shie Mannor

JMLR 2012 Integrating a Partial Model into Model Free Reinforcement Learning Aviv Tamar, Dotan Di Castro, Ron Meir

ICML 2012 Policy Gradients with Variance Related Risk Criteria Dotan Di Castro, Aviv Tamar, Shie Mannor

ICML 2011 Integrating Partial Model Knowledge in Model Free RL Algorithms Aviv Tamar, Dotan Di Castro, Ron Meir