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Scalable Batch Acquisition for Deep Bayesian Active Learning


Jan 13, 2023
Aleksandr Rubashevskii, Daria Kotova, Maxim Panov

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* Accepted to SIAM International Conference on Data Mining 2023 

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Active Learning for Abstractive Text Summarization


Jan 09, 2023
Akim Tsvigun, Ivan Lysenko, Danila Sedashov, Ivan Lazichny, Eldar Damirov, Vladimir Karlov, Artemy Belousov, Leonid Sanochkin, Maxim Panov, Alexander Panchenko, Mikhail Burtsev, Artem Shelmanov

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* Accepted at EMNLP-2022 Findings 

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ScaleFace: Uncertainty-aware Deep Metric Learning


Sep 12, 2022
Roman Kail, Kirill Fedyanin, Nikita Muravev, Alexey Zaytsev, Maxim Panov

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Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective


Jun 21, 2022
Gleb Bazhenov, Sergei Ivanov, Maxim Panov, Alexey Zaytsev, Evgeny Burnaev

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* ICML 2022 PODS Workshop 

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Scalable computation of prediction intervals for neural networks via matrix sketching


May 06, 2022
Alexander Fishkov, Maxim Panov

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Embedded Ensembles: Infinite Width Limit and Operating Regimes


Feb 24, 2022
Maksim Velikanov, Roman Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky

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NUQ: Nonparametric Uncertainty Quantification for Deterministic Neural Networks


Feb 07, 2022
Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Aleksandr Petiushko, Maxim Panov

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Ex$^2$MCMC: Sampling through Exploration Exploitation


Nov 04, 2021
Evgeny Lagutin, Daniil Selikhanovych, Achille Thin, Sergey Samsonov, Alexey Naumov, Denis Belomestny, Maxim Panov, Eric Moulines

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Monte Carlo Variational Auto-Encoders


Jun 30, 2021
Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov

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Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees


Dec 31, 2020
Achille Thin, Nikita Kotolevskii, Christophe Andrieu, Alain Durmus, Eric Moulines, Maxim Panov

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* Submitted to AISTAT 2021 

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