World's Best Scientists 2026 revealed!

Overview

Aviv Tamar is affiliated with the Technion - Israel Institute of Technology in Israel and has contributed extensively to the field of computer science. Their research spans several subfields, with a primary focus on artificial intelligence, computer vision and pattern recognition, control and systems engineering, aerospace engineering, and computer networks and communications.

The scientist's work covers multiple topics, emphasizing reinforcement learning in robotics, adversarial robustness in machine learning, machine learning and data classification, domain adaptation and few-shot learning, generative adversarial networks and image synthesis, anomaly detection techniques and applications, and machine learning algorithms.

Among their recent papers are:

  • "Hallucinative Topological Memory for Zero-Shot Visual Planning," 2020, published in arXiv (Cornell University)
  • "Offline Meta Learning of Exploration," 2020, published in arXiv (Cornell University)
  • "Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning," 2020, published in arXiv (Cornell University)
  • "Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN," 2024, published in arXiv (Cornell University)
  • "Validate on Sim, Detect on Real - Model Selection for Domain Randomization," 2022, presented at the 2022 International Conference on Robotics and Automation (ICRA)

Aviv Tamar has collaborated frequently with several researchers, including:

  • Daniel Tal
  • Tom Jurgenson
  • Ev Zisselman
  • Gal Leibovich
  • Guy Jacob

Their publication record shows a strong presence on arXiv, with 32 papers published in the arXiv repository affiliated with Cornell University. Other venues where Aviv Tamar has published include the 2022 International Conference on Robotics and Automation (ICRA), Nature Communications, Proceedings of the AAAI Conference on Artificial Intelligence, and bioRxiv (Cold Spring Harbor Laboratory).

The broad distribution of research topics and publication venues reflects an interdisciplinary approach grounded primarily in computer science and artificial intelligence, with applications in robotics and machine learning.

Best Publications

  • Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

    Ryan Lowe;Yi Wu;Aviv Tamar;Jean Harb

  • Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

    Ryan Lowe;Yi Wu;Aviv Tamar;Jean Harb

  • Constrained policy optimization

    Joshua Achiam;David Held;Aviv Tamar;Pieter Abbeel

  • Value iteration networks

    Aviv Tamar;Yi Wu;Garrett Thomas;Sergey Levine

  • Bayesian Reinforcement Learning: A Survey

    Mohammad Ghavamzadeh;Shie Mannor;Joelle Pineau;Aviv Tamar

  • Model-Ensemble Trust-Region Policy Optimization

    Thanard Kurutach;Ignasi Clavera;Yan Duan;Aviv Tamar

  • Learning to Route

    Asaf Valadarsky;Michael Schapira;Dafna Shahaf;Aviv Tamar

  • A Deep Reinforcement Learning Perspective on Internet Congestion Control

    Nathan Jay;Noga H. Rotman;Brighten Godfrey;Michael Schapira

  • Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly

    Jianlan Luo;Eugen Solowjow;Chengtao Wen;Juan Aparicio Ojea

  • Risk-sensitive and robust decision-making: a CVaR optimization approach

    Yinlam Chow;Aviv Tamar;Shie Mannor;Marco Pavone

  • Learning Robotic Assembly from CAD

    Garrett Thomas;Melissa Chien;Aviv Tamar;Juan Aparicio Ojea

  • Policy Gradients with Variance Related Risk Criteria

    Dotan D. Castro;Aviv Tamar;Shie Mannor

  • Optimizing the CVaR via sampling

    Aviv Tamar;Yonatan Glassner;Shie Mannor

  • Learning plannable representations with causal InfoGAN

    Thanard Kurutach;Aviv Tamar;Ge Yang;Stuart Russell

  • Bayesian Relational Memory for Semantic Visual Navigation

    Yi Wu;Yuxin Wu;Aviv Tamar;Stuart Russell

  • Learning Robotic Manipulation through Visual Planning and Acting.

    Angelina Wang;Thanard Kurutach;Kara Liu;Pieter Abbeel

  • Scaling Up Robust MDPs using Function Approximation

    Aviv Tamar;Shie Mannor;Huan Xu

  • Deep Residual Flow for Out of Distribution Detection

    Ev Zisselman;Aviv Tamar

  • Policy gradient for coherent risk measures

    Aviv Tamar;Yinlam Chow;Mohammad Ghavamzadeh;Shie Mannor

  • Convex Optimization: Algorithms and Complexity

    Mohammed Ghavamzadeh;Shie Mannor;Joelle Pineau;Aviv Tamar

Frequent Co-Authors

Shie Mannor
Shie Mannor Technion – Israel Institute of Technology
Pieter Abbeel
Pieter Abbeel University of California, Berkeley
Michael Schapira
Michael Schapira Hebrew University of Jerusalem
Sergey Levine
Sergey Levine University of California, Berkeley
Mohammad Ghavamzadeh
Mohammad Ghavamzadeh Amazon (United States)
Stuart Russell
Stuart Russell University of California, Berkeley
Igor Mordatch
Igor Mordatch Google (United States)
Ron Meir
Ron Meir Technion – Israel Institute of Technology
Marco Pavone
Marco Pavone Stanford University
Joelle Pineau
Joelle Pineau McGill University

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