Igor Babuschkin

According to our database, Igor Babuschkin authored at least 17 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning.

Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals

CoRR, 2023

Formal Mathematics Statement Curriculum Learning.

Stanislas Polu, Jesse Michael Han, Kunhao Zheng, Mantas Baksys, Igor Babuschkin, Ilya Sutskever

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Competition-Level Code Generation with AlphaCode.

Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals

CoRR, 2022

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao

CoRR, 2022

Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets.

Alethea Power, Yuri Burda, Harri Edwards, Igor Babuschkin, Vedant Misra

CoRR, 2022

2021

Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving

CoRR, 2021

Unsupervised Neural Machine Translation with Generative Language Models Only.

Jesse Michael Han, Igor Babuschkin, Harrison Edwards, Arvind Neelakantan, Tao Xu, Stanislas Polu, Alex Ray, Pranav Shyam, Aditya Ramesh, Alec Radford, Ilya Sutskever

CoRR, 2021

Evaluating Large Language Models Trained on Code.

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Joshua Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba

CoRR, 2021

Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Ge Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

SunPy: A Python package for Solar Physics.

Stuart Mumford, Nabil Freij, Steven Christe, Jack Ireland, Florian Mayer, V. Keith Hughitt, Albert J. Shih, Daniel Ryan, Simon Liedtke, David Pérez-Suárez, Pritish Chakraborty, Vishnunarayan K, Andrew Inglis, Punyaslok Pattnaik, Brigitta M. Sipocz, Rishabh Sharma, Andrew Leonard, David Stansby, Russell J. Hewett, Alex Hamilton, Laura Hayes, Asish Panda, Matt Earnshaw, Nitin Choudhary, Ankit Kumar, Prateek Chanda, Md. Akramul Haque, Michael Kirk, Michael Mueller, Sudarshan Konge, Rajul Srivastava, Yash Jain, Samuel Bennett, Ankit Baruah, Will T. Barnes, Michael Charlton, Shane A. Maloney, Nicky Chorley, Himanshu, Sanskar Modi, James Mason, Jose Rozo, Larry Manley, Agneet Chatterjee, John Evans, Michael Malocha, Monica G. Bobra, Sourav Ghosh, Dominik Stanczak, Ruben De Visscher, Shresth Verma, Ankit Agrawal, Dumindu Buddhika, Swapnil Sharma, Jongyeob Park, Matt Bates, Dhruv Goel, Garrison Taylor, Goran Cetusic, Jacob, Mateo Inchaurrandieta, Sally Dacie, Sanjeev Dubey, Deepankar Sharma, Erik Bray, Jai Rideout, Serge Zahniy, Tomas Meszaros, Abhigyan Bose, André Chicrala, Ankit, Chloé Guennou, Daniel D'avella, Daniel Williams, Jordan Ballew, Nick Murphy, Priyank Lodha, Thomas Robitaille, Yash Krishan, Andrew Hill, Arthur Eigenbrot, Benjamin Mampaey, Bernhard Wiedemann, Carlos Molina, Duygu Keskek, Ishtyaq Habib, Joseph Letts, Juanjo Bazán, Quinn Arbolante, Reid Gomillion, Yash Kothari, Yash Sharma, Abigail Stevens, Adrian M. Price-Whelan, Ambar Mehrotra, Arseniy Kustov, Brandon Stone, Trung Dang, Emmanuel Arias, Fionnlagh Dover, Freek Verstringe, Gulshan Kumar, Harsh Mathur, Igor Babuschkin, Jaylen Wimbish, Juan Buitrago-Casas, Kalpesh Krishna, Kaustubh Hiware, Manas Mangaonkar, Matthew Mendero, Mickaël Schoentgen, Norbert Gyenge, Ole Streicher, Rajasekhar Mekala, Rishabh Mishra, Shashank Srikanth, Sarthak Jain, Tannmay Yadav, Tessa Wilkinson, Tiago Pereira, Yudhik Agrawal, Jamescalixto, Yasintoda, Sophie Murray

J. Open Source Softw., 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver

Nat., 2019

Unsupervised Doodling and Painting with Improved SPIRAL.

John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami

CoRR, 2019

Deep reinforcement learning with relational inductive biases.

Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Relational Deep Reinforcement Learning.

Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia

CoRR, 2018

Parallel WaveNet: Fast High-Fidelity Speech Synthesis.

Aäron van den Oord, Yazhe Li, Igor Babuschkin, Karen Simonyan, Oriol Vinyals, Koray Kavukcuoglu, George van den Driessche, Edward Lockhart, Luis C. Cobo, Florian Stimberg, Norman Casagrande, Dominik Grewe, Seb Noury, Sander Dieleman, Erich Elsen, Nal Kalchbrenner, Heiga Zen, Alex Graves, Helen King, Tom Walters, Dan Belov, Demis Hassabis

Proceedings of the 35th International Conference on Machine Learning, 2018

Synthesizing Programs for Images using Reinforced Adversarial Learning.

Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Everware toolkit. Supporting reproducible science and challenge-driven education.

Andrey Ustyuzhanin, Timothy Daniel Head, Igor Babuschkin, Alexander Tiunov

CoRR, 2017