Sergey Bartunov

Publication Activity (10 Years)

Years Active: 2011-2022
Publications (10 Years): 20

Top Topics

Mixed Integer Program

Cardinality Estimation

Biologically Motivated

Top Venues

Publications

Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap
Equilibrium Aggregation: Encoding Sets via Optimization. CoRR (2022)
Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap
Equilibrium aggregation: encoding sets via optimization. UAI (2022)
Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti
Computer-Aided Design as Language. NeurIPS (2021)
Nicolas Sonnerat, Pengming Wang, Ira Ktena, Sergey Bartunov, Vinod Nair
Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs. CoRR (2021)
Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti
Computer-Aided Design as Language. CoRR (2021)
Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap
Meta-Learning Deep Energy-Based Memory Models. ICLR (2020)
Vinod Nair, Sergey Bartunov, Felix Gimeno, Ingrid von Glehn, Pawel Lichocki, Ivan Lobov, Brendan O'Donoghue, Nicolas Sonnerat, Christian Tjandraatmadja, Pengming Wang, Ravichandra Addanki, Tharindi Hapuarachchi, Thomas Keck, James Keeling, Pushmeet Kohli, Ira Ktena, Yujia Li, Oriol Vinyals, Yori Zwols
Solving Mixed Integer Programs Using Neural Networks. CoRR (2020)
Jack W. Rae, Sergey Bartunov, Timothy P. Lillicrap
Meta-Learning Neural Bloom Filters. CoRR (2019)
Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap
Meta-Learning Deep Energy-Based Memory Models. CoRR (2019)
Jack W. Rae, Sergey Bartunov, Timothy P. Lillicrap
Meta-Learning Neural Bloom Filters. ICML (2019)
Sergey Bartunov, Adam Santoro, Blake A. Richards, Geoffrey E. Hinton, Timothy P. Lillicrap
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures. CoRR (2018)
Sergey Bartunov, Adam Santoro, Blake A. Richards, Luke Marris, Geoffrey E. Hinton, Timothy P. Lillicrap
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures. NeurIPS (2018)
Sergey Bartunov, Dmitry P. Vetrov
Few-shot Generative Modelling with Generative Matching Networks. AISTATS (2018)
Sergey Bartunov, Dmitry P. Vetrov
Fast Adaptation in Generative Models with Generative Matching Networks. ICLR (Workshop) (2017)
Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John P. Agapiou, Julian Schrittwieser, John Quan, Stephen Gaffney, Stig Petersen, Karen Simonyan, Tom Schaul, Hado van Hasselt, David Silver, Timothy P. Lillicrap, Kevin Calderone, Paul Keet, Anthony Brunasso, David Lawrence, Anders Ekermo, Jacob Repp, Rodney Tsing
StarCraft II: A New Challenge for Reinforcement Learning. CoRR (2017)
Oleg Ivanov, Sergey Bartunov
Adaptive Cardinality Estimation. CoRR (2017)
Sergey Bartunov, Dmitry P. Vetrov
Fast Adaptation in Generative Models with Generative Matching Networks. CoRR (2016)
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov
Breaking Sticks and Ambiguities with Adaptive Skip-gram. AISTATS (2016)
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy P. Lillicrap
Meta-Learning with Memory-Augmented Neural Networks. ICML (2016)
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy P. Lillicrap
One-shot Learning with Memory-Augmented Neural Networks. CoRR (2016)
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov
Breaking Sticks and Ambiguities with Adaptive Skip-gram. CoRR (2015)
Sergey Bartunov, Dmitry P. Vetrov
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process. ICML (2014)
Sergey Bartunov, Alexander Boldakov, Denis Turdakov
WikifyMe: Creating Testbed for Wikifers. SYRCoDIS (2011)