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Subset-Conditioned Generation Using Variational Autoencoder With A Learnable Tensor-Train Induced Prior

M. Kuznetsov, D. Polykovskiy, D. Vetrov, and A. Zhebrak. (2018)

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Daniil Karapetyan

Daniil Verbitskiy

Daniil Roubanov

Daniil Nekrassov

Dimitra Daniil

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Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models.D. Polykovskiy, A. Zhebrak, B. Sánchez-Lengeling, S. Golovanov, O. Tatanov, S. Belyaev, R. Kurbanov, A. Artamonov, V. Aladinskiy, M. Veselov and 4 other author(s). CoRR, (2018)ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks.I. Kemaev, D. Polykovskiy, and D. Vetrov. ACML, volume 95 of Proceedings of Machine Learning Research, page 422-437. PMLR, (2018)Concorde: Morphological Agreement in Conversational Models.D. Polykovskiy, D. Soloviev, and S. Nikolenko. ACML, volume 95 of Proceedings of Machine Learning Research, page 407-421. PMLR, (2018)Extracting Invariant Features From Images Using An Equivariant Autoencoder.D. Kuzminykh, D. Polykovskiy, and A. Zhebrak. ACML, volume 95 of Proceedings of Machine Learning Research, page 438-453. PMLR, (2018)Subset-Conditioned Generation Using Variational Autoencoder With A Learnable Tensor-Train Induced PriorM. Kuznetsov, D. Polykovskiy, D. Vetrov, and A. Zhebrak. (2018)Deterministic Decoding for Discrete Data in Variational Autoencoders.D. Polykovskiy, and D. Vetrov. AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3046-3056. PMLR, (2020)A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models.M. Kuznetsov, D. Polykovskiy, D. Vetrov, and A. Zhebrak. NeurIPS, page 4104-4114. (2019)Chemistry42: An AI-Driven Platform for Molecular Design and Optimization.Y. Ivanenkov, D. Polykovskiy, D. Bezrukov, B. Zagribelnyy, V. Aladinskiy, P. Kamya, A. Aliper, F. Ren, and A. Zhavoronkov. J. Chem. Inf. Model., 63 (3): 695-701 (February 2023)Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS.M. Vakili, C. Gorgulla, A. Nigam, D. Bezrukov, D. Varoli, A. Aliper, D. Polykovskiy, K. Das, J. Snider, A. Lyakisheva and 12 other author(s). CoRR, (2024)nach0: Multimodal Natural and Chemical Languages Foundation Model.M. Livne, Z. Miftahutdinov, E. Tutubalina, M. Kuznetsov, D. Polykovskiy, A. Brundyn, A. Jhunjhunwala, A. Costa, A. Aliper, and A. Zhavoronkov. CoRR, (2023)

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Disambiguation of "Polykovskiy, Daniil"

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Subset-Conditioned Generation Using Variational Autoencoder With A Learnable Tensor-Train Induced Prior

Please choose a person to relate this publication to

Daniil Karapetyan

Daniil Verbitskiy

Daniil Roubanov

Daniil Nekrassov

Dimitra Daniil

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Polykovskiy, Daniil"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Subset-Conditioned Generation Using Variational Autoencoder With A Learnable Tensor-Train Induced Prior

Please choose a person to relate this publication to

Daniil Karapetyan

Daniil Verbitskiy

Daniil Roubanov

Daniil Nekrassov

Dimitra Daniil

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Subset-Conditioned Generation Using Variational Autoencoder With A Learnable Tensor-Train Induced Prior