Abbas Abdolmaleki
Reinforcement Learning · 2017–2025
A researcher in the Science corpus: 11 papers; trusts 108 researchers and is trusted by 47 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 311 citations into it; #438 of 2,242 by trust here, #282 by citations
- Artificial Intelligence — 282 citations into it; #6,925 of 35,345 by trust here, #4,656 by citations
- Control and Systems Engineering — 64 citations into it
- Management Science and Operations Research — 57 citations into it
- Computational Theory and Mathematics — 55 citations into it; #6,717 of 12,182 by trust here, #1,269 by citations
- Computer Vision and Pattern Recognition — 52 citations into it
- Optimization & Training — 40 citations into it
- Electrical and Electronic Engineering — 26 citations into it; #15,624 of 16,539 by trust here, #7,175 by citations
Whom Abbas Abdolmaleki trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John Schulman
- Sergey Levine
- Richard S. Sutton
- Geoffrey E. Hinton
- Jan Peters
- Diederik P. Kingma
- Volodymyr Mnih
- Gerhard Neumann
- Pieter Abbeel
- E. Todorov
Who trusts Abbas Abdolmaleki overall
- Sergey Levine
- Emilio Parisotto
- Josh Merel
- Ofir Nachum
- Gabriel Dulac-Arnold
- Caglar Gulcehre
- Ziyun Wang
- Cosmin Paduraru
- H. Francis Song
- Ruslan Salakhutdinov
Papers from Abbas Abdolmaleki's perspective
Ordered by how strongly the researchers Abbas Abdolmaleki trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- GENERATIVE ADVERSARIAL NETS
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Maximum a Posteriori Policy Optimisation (2018) — 593 citations
- V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control (2019) — 141 citations
- Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning (2020) — 303 citations
- Acme: A Research Framework for Distributed Reinforcement Learning (2020) — 248 citations
- A Distributional View on Multi-Objective Policy Optimization (2020) — 94 citations
- Deriving and improving CMA-ES with information geometric trust regions (2017) — 38 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Magnetic control of tokamak plasmas through deep reinforcement learning (2022) — 923 citations
- From Motor Control to Team Play in Simulated Humanoid Football (2021) — 163 citations
- Regularized Hierarchical Policies for Compositional Transfer in Robotics (2019) — 27 citations
- DeepMind Control Suite (2018) — 1,440 citations