Maruan Al-Shedivat

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Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Jakob FoersterAssociate Professor, University of OxfordVerified email at eng.ox.ac.uk
Gert CauwenberghsProfessor of Bioengineering and Co-Director, Institute for Neural Computation, UC San DiegoVerified email at ucsd.edu
Shimon WhitesonProfessor of Computer Science, University of Oxford / Senior Staff Research Scientist, WaymoVerified email at cs.ox.ac.uk
Emre NeftciInstitute Director, Forschungszentrum Jülich; Professor, RWTH AachenVerified email at fz-juelich.de
Khaled Nabil SalamaKing Abdullah Univeristy of Science and Technology (KAUST)Verified email at kaust.edu.sa
Igor MordatchGoogle DeepMindVerified email at google.com
Pieter AbbeelUC Berkeley | CovariantVerified email at cs.berkeley.edu
Yuri BurdaOpenAIVerified email at openai.com
Aditya GroverAssistant Professor of Computer Science, UCLAVerified email at cs.ucla.edu
Zhiting HuAssistant Professor at UC San DiegoVerified email at ucsd.edu
Ilya SutskeverCo-Founder and Chief Scientist at Safe Superintelligence IncVerified email at ssi.inc
Bowen TanCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Ameet TalwalkarCMU, DatadogVerified email at cmu.edu
Andrew Gordon WilsonNew York UniversityVerified email at cims.nyu.edu
Afshin RostamizadehGoogle ResearchVerified email at google.com
Ankur P ParikhStaff Research Scientist at Google DeepMindVerified email at google.com
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Blaise Aguera y ArcasVP Engineering Fellow, Google ResearchVerified email at google.com
Xin GaoProfessor, Computer Sciences; Director, Computational Bioscience Research CenterVerified email at kaust.edu.sa

Maruan Al-Shedivat

Genesis Therapeutics

Verified email at genesistherapeutics.ai - Homepage

Artificial Intelligence Machine Learning


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Learning with opponent-learning awareness JN Foerster, RY Chen, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch Proceedings of the 17th International Conference on Autonomous Agents and …, 2018	671	2018
Continuous adaptation via meta-learning in nonstationary and competitive environments M Al-Shedivat, T Bansal, Y Burda, I Sutskever, I Mordatch, P Abbeel Proceedings of 6th International Conference on Learning Representations, 2018	431	2018
A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021	423	2021
Stochastic synapses enable efficient brain-inspired learning machines EO Neftci, BU Pedroni, S Joshi, M Al-Shedivat, G Cauwenberghs Frontiers in neuroscience 10, 2016	159	2016
Memristors empower spiking neurons with stochasticity M Al-Shedivat, R Naous, G Cauwenberghs, KN Salama IEEE journal on Emerging and selected topics in circuits and systems 5 (2 …, 2015	145	2015
Learning scalable deep kernels with recurrent structure M Al-Shedivat, AG Wilson, Y Saatchi, Z Hu, EP Xing Journal of Machine Learning Research 18 (82), 1-37, 2017	135	2017
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms M Al-Shedivat, J Gillenwater, E Xing, A Rostamizadeh Proceedings of the 9th International Conference on Learning Representations, 2021	133	2021
Learning Policy Representations in Multiagent Systems A Grover, M Al-Shedivat, JK Gupta, Y Burda, H Edwards Proceedings of the 35th International Conference on Machine Learning 80 …, 2018	127	2018
Stochasticity modeling in memristors R Naous, M Al-Shedivat, KN Salama IEEE Transactions on Nanotechnology 15 (1), 15-28, 2015	121	2015
Contextual Explanation Networks M Al-Shedivat, A Dubey, EP Xing Journal of Machine Learning Research 21 (194), 1−44, 2020	112	2020
DiCE: The Infinitely Differentiable Monte-Carlo Estimator J Foerster, G Farquhar, M Al-Shedivat, T Rocktäschel, EP Xing, ... Proceedings of the 35th International Conference on Machine Learning 80 …, 2018	111	2018
Progressive Generation of Long Text with Pretrained Language Models B Tan, Z Yang, M Al-Shedivat, E Xing, Z Hu Proceedings of the 2021 Conference of the North American Chapter of the …, 2021	110*	2021
Regularizing black-box models for improved interpretability G Plumb, M Al-Shedivat, ÁA Cabrera, A Perer, E Xing, A Talwalkar Advances in Neural Information Processing Systems 33, 10526-10536, 2020	95*	2020
Consistency by agreement in zero-shot neural machine translation M Al-Shedivat, AP Parikh Conference of the North American Chapter of the Association for …, 2019	67	2019
Memristor-based neural networks: Synaptic versus neuronal stochasticity R Naous, M AlShedivat, E Neftci, G Cauwenberghs, KN Salama Aip Advances 6 (11), 2016	41	2016
On Data Efficiency of Meta-learning M Al-Shedivat, L Li, E Xing, A Talwalkar Proceedings of the 24th International Conference on Artificial Intelligence …, 2021	33	2021
Inherently stochastic spiking neurons for probabilistic neural computation M Al-Shedivat, R Naous, E Neftci, G Cauwenberghs, KN Salama 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), 356-359, 2015	33*	2015
Supervised transfer sparse coding M Al-Shedivat, JJY Wang, M Alzahrani, J Huang, X Gao Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014	31	2014
ADIOS: Architectures Deep In Output Space M Cissé, M Al-Shedivat, S Bengio Proceedings of The 33rd International Conference on Machine Learning, 2770-2779, 2016	27	2016
Maruan Al-Shedivat, Jayesh Gupta, Yuri Burda, and Harrison Edwards. Learning policy representations in multiagent systems A Grover International conference on machine learning, 1802-1811, 0	25

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