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ORCIDLeonid Zhukov
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2020 – today
- 2024
[c21]Maksim Golyadkin, Vitaliy Pozdnyakov, Leonid Zhukov, Ilya Makarov:
SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes (Abstract Reprint). IJCAI 2024: 8479- [c20]Maksim Golyadkin, Maria Shtark, Petr Ivanov, Alexander Kozhevnikov, Leonid Zhukov, Ilya Makarov:
Plug-and-Play Unsupervised Fault Detection and Diagnosis for Complex Industrial Monitoring. IJCAI 2024: 8669-8673 - [i10]Julien Delile, Srayanta Mukherjee, Anton Van Pamel, Leonid Zhukov:
Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge. CoRR abs/2402.12352 (2024) - 2023
- [j7]Maksim Golyadkin, Vitaliy Pozdnyakov
, Leonid Zhukov, Ilya Makarov:
SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes. Artif. Intell. 324: 104012 (2023) - 2022
- [j6]Alexander Ponomarchuk, Ilya Burenko, Elian Malkin, Ivan Nazarov, Vladimir Kokh, Manvel Avetisian, Leonid Zhukov:
Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough. IEEE J. Sel. Top. Signal Process. 16(2): 175-187 (2022) - [c19]Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov, Alexander Panchenko, Gleb Gusev, Mikhail Burtsev, Manvel Avetisian, Leonid Zhukov:
Uncertainty Estimation of Transformer Predictions for Misclassification Detection. ACL (1) 2022: 8237-8252 - [c18]Akim Tsvigun, Artem Shelmanov, Gleb Kuzmin, Leonid Sanochkin, Daniil Larionov, Gleb Gusev, Manvel Avetisian, Leonid Zhukov:
Towards Computationally Feasible Deep Active Learning. NAACL-HLT (Findings) 2022: 1198-1218 - [i9]Mikhail E. Belkin, Leonid Zhukov, Alexander S. Sigov:
Advanced service data provisioning in ROF-based mobile backhauls/fronthauls. CoRR abs/2202.02458 (2022) - [i8]Akim Tsvigun, Artem Shelmanov, Gleb Kuzmin, Leonid Sanochkin, Daniil Larionov, Gleb Gusev, Manvel Avetisian, Leonid Zhukov:
Towards Computationally Feasible Deep Active Learning. CoRR abs/2205.03598 (2022) - [i7]Semen A. Budennyy, Vladimir D. Lazarev, Nikita Zakharenko, Alexey N. Korovin, Olga Plosskaya, Denis Dimitrov, Vladimir Arkhipkin, Ivan V. Oseledets, Ivan Barsola, Ilya Egorov, Aleksandra Kosterina, Leonid Zhukov:
Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI. CoRR abs/2208.00406 (2022) - [i6]Alexey N. Korovin, Artem I. Vasilyev, Fedor Egorov, Dmitry Saykin, Evgeny Terukov, Igor Shakhray, Leonid Zhukov, Semen A. Budennyy:
Anomaly segmentation model for defects detection in electroluminescence images of heterojunction solar cells. CoRR abs/2208.05994 (2022) - [i5]Semen A. Budennyy, Alexey Kazakov, Elizaveta Kovtun, Leonid Zhukov:
New drugs and stock market: how to predict pharma market reaction to clinical trial announcements. CoRR abs/2208.07248 (2022) - [i4]Maksim Golyadkin, Vitaliy Pozdnyakov, Leonid Zhukov, Ilya Makarov:
SensorSCAN: Self-Supervised Learning and Deep Clustering for Fault Diagnosis in Chemical Processes. CoRR abs/2208.08879 (2022) - 2021
- [j5]Ildar Lomov, Mark Lyubimov, Ilya Makarov, Leonid E. Zhukov:
Fault detection in Tennessee Eastman process with temporal deep learning models. J. Ind. Inf. Integr. 23: 100216 (2021) - [i3]Alexander Ponomarchuk, Ilya Burenko, Elian Malkin, Ivan Nazarov, Vladimir Kokh, Manvel Avetisian, Leonid Zhukov:
Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough. CoRR abs/2107.10716 (2021)
2010 – 2019
- 2019
- [j4]Ilya Makarov, Olga Gerasimova, Pavel Sulimov, Leonid E. Zhukov:
Dual network embedding for representing research interests in the link prediction problem on co-authorship networks. PeerJ Comput. Sci. 5: e172 (2019) - 2018
- [c17]Ilya Makarov, Olga Gerasimova, Pavel Sulimov, Ksenia Korovina, Leonid E. Zhukov:
Joint Node-Edge Network Embedding for Link Prediction. AIST 2018: 20-31 - [c16]Ilya Makarov, Olga Gerasimova, Pavel Sulimov, Leonid E. Zhukov:
Co-authorship Network Embedding and Recommending Collaborators via Network Embedding. AIST 2018: 32-38 - [c15]Ilya Makarov, Olga Gerasimova, Pavel Sulimov, Leonid E. Zhukov:
Recommending Co-authorship via Network Embeddings and Feature Engineering: The case of National Research University Higher School of Economics. JCDL 2018: 365-366 - 2017
- [c14]Ilya Makarov, Oleg Bulanov, Olga Gerasimova, Natalia Meshcheryakova, Ilia Karpov, Leonid E. Zhukov:
Scientific Matchmaker: Collaborator Recommender System. AIST 2017: 404-410 - [c13]Anvar Kurmukov, Marina Ananyeva, Yulia Dodonova, Boris Gutman, Joshua Faskowitz, Neda Jahanshad, Paul M. Thompson, Leonid Zhukov:
Classifying Phenotypes Based on the Community Structure of Human Brain Networks. GRAIL/MFCA/MICGen@MICCAI 2017: 3-11 - 2016
- [c12]Anvar Kurmukov, Yulia Dodonova, Leonid Zhukov:
Classification of Normal and Pathological Brain Networks Based on Similarity in Graph Partitions. ICDM Workshops 2016: 107-112 - [c11]Yulia Dodonova, Sergey Korolev, Anna Tkachev, Dmitry Petrov, Leonid Zhukov, Mikhail Belyaev:
Classification of structural brain networks based on information divergence of graph spectra. MLSP 2016: 1-6 - [c10]Dmitry Petrov, Yulia Dodonova, Leonid Zhukov, Mikhail Belyaev:
Boosting connectome classification via combination of geometric and topological normalizations. PRNI 2016: 1-4 - [i2]Yulia Dodonova, Mikhail Belyaev, Anna Tkachev, Dmitry Petrov, Leonid Zhukov:
Kernel classification of connectomes based on earth mover's distance between graph spectra. CoRR abs/1611.08812 (2016) - 2014
- [c9]Jeffrey Sukharev, Leonid Zhukov, Alexandrin Popescul:
Parallel Corpus Approach for Name Matching in Record Linkage. ICDM 2014: 995-1000 - [i1]Jeffrey Sukharev, Leonid Zhukov, Alexandrin Popescul:
Learning Alternative Name Spellings. CoRR abs/1405.2048 (2014) - 2013
- [j3]Dmitry I. Ignatov, Sergei O. Kuznetsov, Jonas Poelmans, Leonid E. Zhukov:
Can triconcepts become triclusters? Int. J. Gen. Syst. 42(6): 572-593 (2013) - 2011
- [c8]Dmitry I. Ignatov, Sergei O. Kuznetsov, Ruslan A. Magizov, Leonid E. Zhukov:
From Triconcepts to Triclusters. RSFDGrC 2011: 257-264
2000 – 2009
- 2005
- [p2]Leonid Zhukov, Alan H. Barr:
Oriented Tensor Reconstruction Portions reprinted, with permission, from Zhukov and Barr [26]. Copyright © 2002, IEEE. The Visualization Handbook 2005: 313-326 - 2004
- [j2]Robert Van Uitert, Chris R. Johnson, Leonid Zhukov:
Influence of head tissue conductivity in forward and inverse magnetoencephalographic Simulations using realistic head models. IEEE Trans. Biomed. Eng. 51(12): 2129-2137 (2004) - [c7]David F. Gleich, Leonid Zhukov:
SVD based Term Suggestion and Ranking System. ICDM 2004: 391-394 - [p1]Gary William Flake, Kostas Tsioutsiouliklis, Leonid Zhukov:
Methods for MiningWeb Communities: Bibliometric, Spectral, and Flow. Web Dynamics 2004: 45-68 - 2003
- [j1]Leonid Zhukov, Ken Museth, David E. Breen, Alan H. Barr, Ross T. Whitaker:
Level set modeling and segmentation of diffusion tensor magnetic resonance imaging brain data. J. Electronic Imaging 12(1): 125-133 (2003) - [c6]Leonid Zhukov, Alan H. Barr:
Heart-Muscle Fiber Reconstruction from Diffusion Tensor MRI. IEEE Visualization 2003: 597-602 - 2002
- [c5]Leonid Zhukov, Zhaosheng Bao, Igor Guskov, John Wood, David E. Breen:
Dynamic deformable models for 3D MRI heart segmentation. Medical Imaging: Image Processing 2002 - [c4]Ken Museth, David E. Breen, Leonid Zhukov, Ross T. Whitaker:
Level-Set Segmentation From Multiple Non-Uniform Volume Datasets. IEEE Visualization 2002: 179-186 - [c3]Leonid Zhukov, Alan H. Barr:
Oriented Tensor Reconstruction: Tracing Neural Pathways from Diffusion Tensor MRI. IEEE Visualization 2002: 387-394 - [c2]Igor Guskov, Leonid Zhukov:
Direct Pattern Tracking On Flexible Geometry. WSCG 2002: 203-208 - 2001
- [c1]Leonid Zhukov, Ken Museth, David E. Breen, Ross T. Whitaker:
3D modeling and segmentation of diffusion weighted MRI data. Medical Imaging: Image-Guided Procedures 2001
Coauthor Index
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