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Sergey Bartunov
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2020 – today
- 2022
- [c11]Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap:
Equilibrium aggregation: encoding sets via optimization. UAI 2022: 139-149 - [i12]Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap:
Equilibrium Aggregation: Encoding Sets via Optimization. CoRR abs/2202.12795 (2022) - 2021
- [c10]Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti:
Computer-Aided Design as Language. NeurIPS 2021: 5885-5897 - [i11]Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti:
Computer-Aided Design as Language. CoRR abs/2105.02769 (2021) - [i10]Nicolas Sonnerat, Pengming Wang, Ira Ktena, Sergey Bartunov, Vinod Nair:
Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs. CoRR abs/2107.10201 (2021) - 2020
- [c9]Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap:
Meta-Learning Deep Energy-Based Memory Models. ICLR 2020 - [i9]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 abs/2012.13349 (2020)
2010 – 2019
- 2019
- [c8]Jack W. Rae, Sergey Bartunov, Timothy P. Lillicrap:
Meta-Learning Neural Bloom Filters. ICML 2019: 5271-5280 - [i8]Jack W. Rae, Sergey Bartunov, Timothy P. Lillicrap:
Meta-Learning Neural Bloom Filters. CoRR abs/1906.04304 (2019) - [i7]Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap:
Meta-Learning Deep Energy-Based Memory Models. CoRR abs/1910.02720 (2019) - 2018
- [c7]Sergey Bartunov, Dmitry P. Vetrov:
Few-shot Generative Modelling with Generative Matching Networks. AISTATS 2018: 670-678 - [c6]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: 9390-9400 - [i6]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 abs/1807.04587 (2018) - 2017
- [c5]Sergey Bartunov, Dmitry P. Vetrov:
Fast Adaptation in Generative Models with Generative Matching Networks. ICLR (Workshop) 2017 - [i5]Oriol Vinyals, Timo Ewalds
StarCraft II: A New Challenge for Reinforcement Learning. CoRR abs/1708.04782 (2017) - [i4]Oleg Ivanov, Sergey Bartunov:
Adaptive Cardinality Estimation. CoRR abs/1711.08330 (2017) - 2016
- [c4]Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov:
Breaking Sticks and Ambiguities with Adaptive Skip-gram. AISTATS 2016: 130-138 - [c3]Adam Santoro, Sergey Bartunov, Matthew M. Botvinick, Daan Wierstra, Timothy P. Lillicrap:
Meta-Learning with Memory-Augmented Neural Networks. ICML 2016: 1842-1850 - [i3]Adam Santoro, Sergey Bartunov, Matthew M. Botvinick, Daan Wierstra, Timothy P. Lillicrap:
One-shot Learning with Memory-Augmented Neural Networks. CoRR abs/1605.06065 (2016) - [i2]Sergey Bartunov, Dmitry P. Vetrov:
Fast Adaptation in Generative Models with Generative Matching Networks. CoRR abs/1612.02192 (2016) - 2015
- [i1]Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov:
Breaking Sticks and Ambiguities with Adaptive Skip-gram. CoRR abs/1502.07257 (2015) - 2014
- [c2]Sergey Bartunov, Dmitry P. Vetrov:
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process. ICML 2014: 1404-1412 - 2011
- [c1]Sergey Bartunov, Alexander Boldakov, Denis Turdakov:
WikifyMe: Creating Testbed for Wikifers. SYRCoDIS 2011: 38-42
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