Alexander Novikov

40 papers A* 5A 1Misc 1Journal 29Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ArchAgent: Agentic AI-driven Computer Architecture Discovery. CoRR Raghav Gupta, Akanksha Jain, Abraham Gonzalez, Alexander Novikov, Po-Sen Huang, Matej Balog, Marvin Eisenberger, Sergey Shirobokov, Ngân Vu, Martin Dixon, Borivoje Nikolic, Parthasarathy Ranganathan, Sagar Karandikar
2026	J	`jnl`	Magellan: Autonomous Discovery of Novel Compiler Optimization Heuristics with AlphaEvolve. CoRR Hongzheng Chen, Alexander Novikov, Ngân Vu, Hanna Alam, Zhiru Zhang, Aiden Grossman, Mircea Trofin, Amir Yazdanbakhsh
2025	J	`jnl`	AlphaEvolve: A coding agent for scientific and algorithmic discovery. CoRR Alexander Novikov, Ngân Vu, Marvin Eisenberger, Emilien Dupont, Po-Sen Huang, Adam Zsolt Wagner, Sergey Shirobokov, Borislav Kozlovskii, Francisco J. R. Ruiz, Abbas Mehrabian, M. Pawan Kumar, Abigail See, Swarat Chaudhuri, George Holland, Alex Davies, Sebastian Nowozin, Pushmeet Kohli, Matej Balog
2025	A*	`conf`	Discovering Symbolic Cognitive Models from Human and Animal Behavior. ICML Pablo Samuel Castro, Nenad Tomasev, Ankit Anand, Navodita Sharma, Rishika Mohanta, Aparna Dev, Kuba Perlin, Siddhant Jain, Kyle Levin, Noémi Élteto, Will Dabney, Alexander Novikov, Glenn C. Turner, Maria K. Eckstein, Nathaniel D. Daw, Kevin J. Miller, Kim Stachenfeld
2025	J	`jnl`	Quantum circuit optimization with AlphaTensor. Nat. Mac. Intell. Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli
2024	J	`jnl`	Amplifying human performance in combinatorial competitive programming. CoRR Petar Velickovic, Alex Vitvitskyi, Larisa Markeeva, Borja Ibarz, Lars Buesing, Matej Balog, Alexander Novikov
2024	J	`jnl`	Mathematical discoveries from program search with large language models. Nat. Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi
2024	J	`jnl`	Quantum Circuit Optimization with AlphaTensor. CoRR Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli
2022	J	`jnl`	A Generalist Agent. CoRR Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas
2022	J	`jnl`	A Generalist Agent. Trans. Mach. Learn. Res. Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas
2022	J	`jnl`	Automatic Differentiation for Riemannian Optimization on Low-Rank Matrix and Tensor-Train Manifolds. SIAM J. Sci. Comput. Alexander Novikov, Maxim V. Rakhuba, Ivan V. Oseledets
2022	J	`jnl`	Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli
2021	J	`jnl`	Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds. CoRR Alexander Novikov, Maxim V. Rakhuba, Ivan V. Oseledets
2021	A*	`conf`	Benchmarks for Deep Off-Policy Evaluation. ICLR Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine
2021	J	`jnl`	Benchmarks for Deep Off-Policy Evaluation. CoRR Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine
2020	J	`jnl`	Acme: A Research Framework for Distributed Reinforcement Learning. CoRR Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal M. P. Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alexander Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas
2020	A*	`conf`	Critic Regularized Regression. NeurIPS Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	Critic Regularized Regression. CoRR Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	Hyperparameter Selection for Offline Reinforcement Learning. CoRR Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas
2020	J	`jnl`	Offline Learning from Demonstrations and Unlabeled Experience. CoRR Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Çaglar Gülçehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott E. Reed
2020	A*	`conf`	RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas
2020	—	`conf`	Scaling data-driven robotics with reward sketching and batch reinforcement learning. Robotics: Science and Systems Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
2020	J	`jnl`	Semi-supervised reward learning for offline reinforcement learning. CoRR Ksenia Konyushkova, Konrad Zolna, Yusuf Aytar, Alexander Novikov, Scott E. Reed, Serkan Cabi, Nando de Freitas
2020	Misc	`conf`	Task-Relevant Adversarial Imitation Learning. CoRL Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
2020	J	`jnl`	Tensor Train Decomposition on TensorFlow (T3F). J. Mach. Learn. Res. Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V. Oseledets
2019	J	`jnl`	A Framework for Data-Driven Robotics. CoRR Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
2019	J	`jnl`	Low-rank Riemannian eigensolver for high-dimensional Hamiltonians. J. Comput. Phys. Maxim V. Rakhuba, Alexander Novikov, Ivan V. Oseledets
2019	J	`jnl`	Task-Relevant Adversarial Imitation Learning. CoRR Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gomez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
2018	—	`conf`	Expressive power of recurrent neural networks. ICLR (Poster) Valentin Khrulkov, Alexander Novikov, Ivan V. Oseledets
2018	A	`conf`	Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. AISTATS Pavel Izmailov, Alexander Novikov, Dmitry Kropotov
2018	J	`jnl`	Tensor Train decomposition on TensorFlow (T3F). CoRR Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V. Oseledets
2017	—	`conf`	Exponential Machines. ICLR (Workshop) Alexander Novikov, Mikhail Trofimov, Ivan V. Oseledets
2017	J	`jnl`	Expressive power of recurrent neural networks. CoRR Valentin Khrulkov, Alexander Novikov, Ivan V. Oseledets
2017	J	`jnl`	Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. CoRR Pavel Izmailov, Alexander Novikov, Dmitry Kropotov
2016	J	`jnl`	Tensor Train polynomial models via Riemannian optimization. CoRR Alexander Novikov, Mikhail Trofimov, Ivan V. Oseledets
2016	J	`jnl`	Ultimate tensorization: compressing convolutional and FC layers alike. CoRR Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, Dmitry P. Vetrov
2015	—	`conf`	Tensorizing Neural Networks. NIPS Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov
2015	J	`jnl`	Tensorizing Neural Networks. CoRR Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov
2014	A*	`conf`	Putting MRFs on a Tensor Train. ICML Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry P. Vetrov