Maxim Panov - RankMe

104 papers A* 13A 6B 2C 4Misc 5Journal 51Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	—	`ed.`	Analysis of Images, Social Networks and Texts - 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17-19, 2024, Revised Selected Papers AIST (Supplement) Alexander Panchenko, Dmitry Gubanov, Michael Yu. Khachay, Andrey Kutuzov, Natalia V. Loukachevitch, Andrey Kuznetsov, Irina Nikishina, Maxim Panov, Panos M. Pardalos, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina, Aida Kasieva, Dmitry I. Ignatov
2026	J	`jnl`	IDLM: Inverse-distilled Diffusion Language Models. CoRR David Li, Nikita Gushchin, Dmitry Abulkhanov, Eric Moulines, Ivan V. Oseledets, Maxim Panov, Alexander Korotin
2026	—	`conf`	Uncertainty Quantification for Large Language Models. ECIR (4) Maxim Panov, Artem Shelmanov, Roman Vashurin, Artem Vazhentsev, Ekaterina Fadeeva, Lyudmila Rvanova, Timothy Baldwin
2025	J	`jnl`	Adaptive Temperature Scaling with Conformal Prediction. CoRR Nikita Kotelevskii, Mohsen Guizani, Eric Moulines, Maxim Panov
2025	Misc	`ed.`	Analysis of Images, Social Networks and Texts - 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17-19, 2024, Revised Selected Papers AIST Alexander Panchenko, Dmitry A. Gubanov, Mikhail Yu. Khachay, Andrey Kutuzov, Natalia V. Loukachevitch, Andrey Kuznetsov, Irina Nikishina, Maxim Panov, Panos M. Pardalos, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina, Aida Kasieva, Dmitry I. Ignatov
2025	J	`jnl`	Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph. Trans. Assoc. Comput. Linguistics Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, Lyudmila Rvanova, Daniil Vasilev, Akim Tsvigun, Sergey Petrakov, Rui Xing, Abdelrahman Boda Sadallah, Kirill Grishchenkov, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov, Artem Shelmanov
2025	J	`jnl`	CoCoA: A Generalized Approach to Uncertainty Quantification by Integrating Confidence and Consistency of LLM Outputs. CoRR Roman Vashurin, Maiya Goloburda, Preslav Nakov, Artem Shelmanov, Maxim Panov
2025	J	`jnl`	Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search. CoRR Ekaterina Fadeeva, Maiya Goloburda, Aleksandr Rubashevskii, Roman Vashurin, Artem Shelmanov, Preslav Nakov, Mrinmaya Sachan, Maxim Panov
2025	J	`jnl`	Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval Augmented Generation. CoRR Ekaterina Fadeeva, Aleksandr Rubashevskii, Roman Vashurin, Shehzaad Dhuliawala, Artem Shelmanov, Timothy Baldwin, Preslav Nakov, Mrinmaya Sachan, Maxim Panov
2025	A*	`conf`	From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation. ICLR Nikita Kotelevskii, Vladimir Kondratyev, Martin Takác, Eric Moulines, Maxim Panov
2025	A	`conf`	Learning Confident Classifiers in the Presence of Label Noise. SDM Asma Ahmed Hashmi, Aigerim Zhumabayeva, Nikita Kotelevskii, Artem Agafonov, Mohammad Yaqub, Maxim Panov, Martin Takác
2025	J	`jnl`	Multidimensional Uncertainty Quantification via Optimal Transport. CoRR Nikita Kotelevskii, Maiya Goloburda, Vladimir Kondratyev, Alexander Fishkov, Mohsen Guizani, Eric Moulines, Maxim Panov
2025	J	`jnl`	Neural Optimal Transport Meets Multivariate Conformal Prediction. CoRR Vladimir Kondratyev, Alexander Fishkov, Nikita Kotelevskii, Mahmoud Hegazy, Rémi Flamary, Maxim Panov, Eric Moulines
2025	A*	`conf`	Probabilistic Conformal Prediction with Approximate Conditional Validity. ICLR Vincent Plassier, Alexander Fishkov, Mohsen Guizani, Maxim Panov, Eric Moulines
2025	A*	`conf`	Rectifying Conformity Scores for Better Conditional Coverage. ICML Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines
2025	J	`jnl`	Rectifying Conformity Scores for Better Conditional Coverage. CoRR Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines
2025	J	`jnl`	Screener: Self-supervised Pathology Segmentation Model for 3D Medical Images. CoRR Mikhail Goncharov, Eugenia Soboleva, Maria Donskova, Ivan V. Oseledets, Marina Munkhoeva, Maxim Panov
2025	—	`conf`	Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models. NAACL (Long Papers) Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
2025	J	`jnl`	Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models. CoRR Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
2025	A*	`conf`	UNCERTAINTY-LINE: Length-Invariant Estimation of Uncertainty for Large Language Models. EMNLP Roman Vashurin, Maiya Goloburda, Preslav Nakov, Maxim Panov
2025	J	`jnl`	UNCERTAINTY-LINE: Length-Invariant Estimation of Uncertainty for Large Language Models. CoRR Roman Vashurin, Maiya Goloburda, Preslav Nakov, Maxim Panov
2025	—	`conf`	Uncertainty Quantification for Large Language Models. ACL (5) Artem Shelmanov, Maxim Panov, Roman Vashurin, Artem Vazhentsev, Ekaterina Fadeeva, Timothy Baldwin
2025	J	`jnl`	Uncertainty Quantification for Regression using Proper Scoring Rules. CoRR Alexander Fishkov, Kajetan Schweighofer, Mykyta Ielanskyi, Nikita Kotelevskii, Mohsen Guizani, Maxim Panov
2025	J	`jnl`	Uncertainty-Aware Attention Heads: Efficient Unsupervised Uncertainty Quantification for LLMs. CoRR Artem Vazhentsev, Lyudmila Rvanova, Gleb Kuzmin, Ekaterina Fadeeva, Ivan Lazichny, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Mrinmaya Sachan, Preslav Nakov, Artem Shelmanov
2025	J	`jnl`	Uncertainty-aware abstention in medical diagnosis based on medical texts. CoRR Artem Vazhentsev, Ivan Sviridov, Alvard Barseghyan, Gleb Kuzmin, Alexander Panchenko, Aleksandr Nesterov, Artem Shelmanov, Maxim Panov
2025	A*	`conf`	Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models. EMNLP Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, Gleb Kuzmin, Ivan Lazichny, Alexander Panchenko, Preslav Nakov, Timothy Baldwin, Maxim Panov, Artem Shelmanov
2025	J	`jnl`	Who to Trust? Aggregating Client Knowledge in Logit-Based Federated Learning. CoRR Viktor Kovalchuk, Nikita Kotelevskii, Maxim Panov, Samuel Horváth, Martin Takác
2024	Misc	`ed.`	Analysis of Images, Social Networks and Texts - 11th International Conference, AIST 2023, Yerevan, Armenia, September 28-30, 2023, Revised Selected Papers AIST Dmitry I. Ignatov, Michael Yu. Khachay, Andrey Kutuzov, Habet Madoyan, Ilya Makarov, Irina Nikishina, Alexander Panchenko, Maxim Panov, Panos M. Pardalos, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina, Sergey Zagoruyko
2024	Misc	`conf`	Automatic Adaptive Conformal Inference for Time Series Forecasting. AIST Artem Makhin, Maxim Panov
2024	J	`jnl`	Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph. CoRR Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, Akim Tsvigun, Daniil Vasilev, Rui Xing, Abdelrahman Boda Sadallah, Lyudmila Rvanova, Sergey Petrakov, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov, Artem Shelmanov
2024	J	`jnl`	Conditionally valid Probabilistic Conformal Prediction. CoRR Vincent Plassier, Alexander Fishkov, Maxim Panov, Eric Moulines
2024	A*	`conf`	Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks. IJCAI Nikita Kotelevskii, Samuel Horváth, Karthik Nandakumar, Martin Takác, Maxim Panov
2024	A	`conf`	Efficient Conformal Prediction under Data Heterogeneity. AISTATS Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
2024	—	`conf`	Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. ACL (Findings) Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
2024	J	`jnl`	Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. CoRR Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
2024	A*	`conf`	Generalization error of spectral algorithms. ICLR Maksim Velikanov, Maxim Panov, Dmitry Yarotsky
2024	J	`jnl`	Generalization error of spectral algorithms. CoRR Maksim Velikanov, Maxim Panov, Dmitry Yarotsky
2024	J	`jnl`	Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules. CoRR Nikita Kotelevskii, Maxim Panov
2024	—	`ed.`	Recent Trends in Analysis of Images, Social Networks and Texts - 11th International Conference, AIST 2023, Yerevan, Armenia, September 28-30, Revised Selected Papers AIST (Supplement) Dmitry I. Ignatov, Michael Yu. Khachay, Andrey Kutuzov, Habet Madoyan, Ilya Makarov, Irina Nikishina, Alexander Panchenko, Maxim Panov, Panos M. Pardalos, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina, Sergey Zagoruyko
2024	—	`conf`	Reference-free Hallucination Detection for Large Vision-Language Models. EMNLP (Findings) Qing Li, Jiahui Geng, Chenyang Lyu, Derui Zhu, Maxim Panov, Fakhri Karray
2024	J	`jnl`	Reference-free Hallucination Detection for Large Vision-Language Models. CoRR Qing Li, Chenyang Lyu, Jiahui Geng, Derui Zhu, Maxim Panov, Fakhri Karray
2024	J	`jnl`	Unconditional Truthfulness: Learning Conditional Dependency for Uncertainty Quantification of Large Language Models. CoRR Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, Alexander Panchenko, Preslav Nakov, Timothy Baldwin, Maxim Panov, Artem Shelmanov
2023	J	`jnl`	Active Learning for Abstractive Text Summarization. CoRR Akim Tsvigun, Ivan Lysenko, Danila Sedashov, Ivan Lazichny, Eldar Damirov, Vladimir Karlov, Artemy Belousov, Leonid Sanochkin, Maxim Panov, Alexander Panchenko, Mikhail Burtsev, Artem Shelmanov
2023	A*	`conf`	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. ICML Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	J	`jnl`	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. CoRR Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	J	`jnl`	Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks. CoRR Nikita Kotelevskii, Samuel Horváth, Karthik Nandakumar, Martin Takác, Maxim Panov
2023	—	`conf`	Distributed Bayesian Coresets. AIST (Supplement) Vladimir Omelyusik, Maxim Panov
2023	J	`jnl`	Efficient Conformal Prediction under Data Heterogeneity. CoRR Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
2023	—	`conf`	Efficient Out-of-Domain Detection for Sequence to Sequence Models. ACL (Findings) Artem Vazhentsev, Akim Tsvigun, Roman Vashurin, Sergey Petrakov, Daniil Vasilev, Maxim Panov, Alexander Panchenko, Artem Shelmanov
2023	—	`conf`	Hybrid Uncertainty Quantification for Selective Text Classification in Ambiguous Tasks. ACL (1) Artem Vazhentsev, Gleb Kuzmin, Akim Tsvigun, Alexander Panchenko, Maxim Panov, Mikhail Burtsev, Artem Shelmanov
2023	—	`conf`	LM-Polygraph: Uncertainty Estimation for Language Models. EMNLP (Demos) Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
2023	J	`jnl`	LM-Polygraph: Uncertainty Estimation for Language Models. CoRR Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
2023	A	`conf`	Learning from Low Rank Tensor Data: A Random Tensor Theory Perspective. UAI Mohamed El Amine Seddik, Malik Tiomoko, Alexis Decurninge, Maxim Panov, Maxime Guillaud
2023	J	`jnl`	Optimal Estimation in Mixed-Membership Stochastic Block Models. CoRR Fedor Noskov, Maxim Panov
2023	—	`conf`	Real-Time Reconstruction of Complex Flow in Nanoporous Media: Linear vs Non-linear Decoding. ICCS (3) Emmanuel Akeweje, Andrey Olhin, Vsevolod Avilkin, Aleksey Vishnyakov, Maxim Panov
2023	A	`conf`	Scalable Batch Acquisition for Deep Bayesian Active Learning. SDM Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
2023	J	`jnl`	Scalable Batch Acquisition for Deep Bayesian Active Learning. CoRR Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
2023	B	`conf`	ScaleFace: Uncertainty-aware Deep Metric Learning. DSAA Roman Kail, Kirill Fedyanin, Nikita Muravev, Alexey Zaytsev, Maxim Panov
2023	C	`conf`	Selective Nonparametric Regression via Testing. ACML Fedor Noskov, Alexander Fishkov, Maxim Panov
2023	J	`jnl`	Selective Nonparametric Regression via Testing. CoRR Fedor Noskov, Alexander Fishkov, Maxim Panov
2023	—	`conf`	Uncertainty Estimation for Debiased Models: Does Fairness Hurt Reliability? IJCNLP (1) Gleb Kuzmin, Artem Vazhentsev, Artem Shelmanov, Xudong Han, Simon Suster, Maxim Panov, Alexander Panchenko, Timothy Baldwin
2022	—	`conf`	Active Learning for Abstractive Text Summarization. EMNLP (Findings) Akim Tsvigun, Ivan Lysenko, Danila Sedashov, Ivan Lazichny, Eldar Damirov, Vladimir Karlov, Artemy Belousov, Leonid Sanochkin, Maxim Panov, Alexander Panchenko, Mikhail Burtsev, Artem Shelmanov
2022	J	`jnl`	Embedded Ensembles: Infinite Width Limit and Operating Regimes. CoRR Maksim Velikanov, Roman Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky
2022	A	`conf`	Embedded Ensembles: infinite width limit and operating regimes. AISTATS Maksim Velikanov, Roman V. Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky
2022	J	`jnl`	NUQ: Nonparametric Uncertainty Quantification for Deterministic Neural Networks. CoRR Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Aleksandr Petiushko, Maxim Panov
2022	A*	`conf`	Nonparametric Uncertainty Quantification for Single Deterministic Neural Network. NeurIPS Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Artem Shelmanov, Artem Vazhentsev, Aleksandr Petiushko, Maxim Panov
2022	J	`jnl`	Scalable computation of prediction intervals for neural networks via matrix sketching. CoRR Alexander Fishkov, Maxim Panov
2022	J	`jnl`	ScaleFace: Uncertainty-aware Deep Metric Learning. CoRR Roman Kail, Kirill Fedyanin, Nikita Muravev, Alexey Zaytsev, Maxim Panov
2022	J	`jnl`	Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective. CoRR Gleb Bazhenov, Sergei Ivanov, Maxim Panov, Alexey Zaytsev, Evgeny Burnaev
2022	—	`conf`	Uncertainty Estimation of Transformer Predictions for Misclassification Detection. ACL (1) Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov, Alexander Panchenko, Gleb Gusev, Mikhail Burtsev, Manvel Avetisian, Leonid Zhukov
2021	—	`conf`	Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling. AIST (Supplement) Kirill Fedyanin, Evgenii Tsymbalov, Maxim Panov
2021	J	`jnl`	Ex CoRR Evgeny Lagutin, Daniil Selikhanovych, Achille Thin, Sergey Samsonov, Alexey Naumov, Denis Belomestny, Maxim Panov, Eric Moulines
2021	A	`conf`	How Certain is Your Transformer? EACL Artem Shelmanov, Evgenii Tsymbalov, Dmitry Puzyrev, Kirill Fedyanin, Alexander Panchenko, Maxim Panov
2021	J	`jnl`	Linking bank clients using graph neural networks powered by rich transactional data. Int. J. Data Sci. Anal. Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov
2021	A*	`conf`	Monte Carlo Variational Auto-Encoders. ICML Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
2021	J	`jnl`	Monte Carlo Variational Auto-Encoders. CoRR Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
2021	—	`conf`	Retrospective on the SENSORIUM 2022 competition. NeurIPS (Competition and Demos) Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri, Laura Hansel, Christoph Blessing, Konstantin-Klemens Lurz, Max F. Burg, Santiago A. Cadena, Zhiwei Ding, Kayla Ponder, Taliah Muhammad, Saumil S. Patel, Kaiwen Deng, Yuanfang Guan, Yiqin Zhu, Kaiwen Xiao, Xiao Han, Simone Azeglio, Ulisse Ferrari, Peter Neri, Olivier Marre, Adrian Hoffmann, Kirill Fedyanin, Kirill Vishniakov, Maxim Panov, Subash Prakash, Kishan Naik, Kantharaju Narayanappa, Alexander S. Ecker, Andreas S. Tolias, Fabian H. Sinz
2021	Misc	`conf`	Scalable Computation of Prediction Intervals for Neural Networks via Matrix Sketching. AIST Alexander Fishkov, Maxim Panov
2020	J	`jnl`	Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampled Implicit Ensembles. CoRR Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov
2020	A*	`conf`	EWS-GCN: Edge Weight-Shared Graph Convolutional Network for Transactional Banking Data. ICDM Ivan Sukharev, Valentina Shumovskaia, Kirill Fedyanin, Maxim Panov, Dmitry Berestnev
2020	J	`jnl`	EWS-GCN: Edge Weight-Shared Graph Convolutional Network for Transactional Banking Data. CoRR Ivan Sukharev, Valentina Shumovskaia, Kirill Fedyanin, Maxim Panov, Dmitry Berestnev
2020	J	`jnl`	Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data. CoRR Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov
2020	B	`conf`	Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data: Extended Abstract. DSAA Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov
2020	J	`jnl`	MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference. CoRR Achille Thin, Nikita Kotelevskii, Jean-Stanislas Denain, Léo Grinsztajn, Alain Durmus, Maxim Panov, Eric Moulines
2020	A*	`conf`	NCVis: Noise Contrastive Approach for Scalable Visualization. WWW Aleksandr Artemenkov, Maxim Panov
2020	J	`jnl`	NCVis: Noise Contrastive Approach for Scalable Visualization. CoRR Aleksandr Artemenkov, Maxim Panov
2019	C	`conf`	Data-Driven Body-Machine Interface for Drone Intuitive Control through Voice and Gestures. IECON Alexander Menshchikov, Dmitry Ermilov, I. Dranitsky, L. Kupchenko, Maxim Panov, Maxim V. Fedorov, Andrey Somov
2019	A*	`conf`	Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning. IJCAI Evgenii Tsymbalov, Sergei Makarychev, Alexander Shapeev, Maxim Panov
2019	J	`jnl`	Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning. CoRR Evgenii Tsymbalov, Sergei Makarychev, Alexander Shapeev, Maxim Panov
2019	C	`conf`	Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension. ACML Marina Gomtsyan, Nikita Mokrov, Maxim Panov, Yury Yanovich
2019	J	`jnl`	Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension. CoRR Marina Gomtsyan, Nikita Mokrov, Maxim Panov, Yury Yanovich
2018	—	`conf`	Constructing Graph Node Embeddings via Discrimination of Similarity Distributions. ICDM Workshops Maxim Panov, Stanislav Tsepa
2018	J	`jnl`	Constructing Graph Node Embeddings via Discrimination of Similarity Distributions. CoRR Stanislav Tsepa, Maxim Panov
2018	Misc	`conf`	Dropout-Based Active Learning for Regression. AIST Evgenii Tsymbalov, Maxim Panov, Alexander Shapeev
2018	J	`jnl`	Dropout-based Active Learning for Regression. CoRR Evgenii Tsymbalov, Maxim Panov, Alexander Shapeev
2018	J	`jnl`	Sparse Group Inductive Matrix Completion. CoRR Ivan Nazarov, Boris Shirokikh, Maria Burkina, Gennady Fedonin, Maxim Panov
2017	C	`conf`	Automatic Bitcoin Address Clustering. ICMLA Dmitry Ermilov, Maxim Panov, Yury Yanovich
2017	—	`conf`	Consistent Estimation of Mixed Memberships with Successive Projections. COMPLEX NETWORKS Maxim Panov, Konstantin Slavnov, Roman Ushakov
2017	—	`conf`	Simultaneous Matrix Diagonalization for Structural Brain Networks Classification. COMPLEX NETWORKS Nikita Mokrov, Maxim Panov, Boris A. Gutman, Joshua I. Faskowitz, Neda Jahanshad, Paul M. Thompson
2016	J	`jnl`	GTApprox: Surrogate modeling for industrial design. Adv. Eng. Softw. Mikhail Belyaev, Evgeny Burnaev, Ermek Kapushev, Maxim Panov, Pavel V. Prikhodko, Dmitry P. Vetrov, Dmitry Yarotsky
2016	J	`jnl`	GTApprox: surrogate modeling for industrial design. CoRR Mikhail Belyaev, Evgeny Burnaev, Ermek Kapushev, Maxim Panov, Pavel V. Prikhodko, Dmitry P. Vetrov, Dmitry Yarotsky
2016	—	`conf`	Overlapping Community Detection in Weighted Graphs: Matrix Factorization Approach. IDP Konstantin Slavnov, Maxim Panov
2015	—	`conf`	Adaptive Design of Experiments Based on Gaussian Processes. SLDS Evgeny Burnaev, Maxim Panov
2011	—	`conf`	A Modified Neutral Point Method for Kernel-Based Fusion of Pattern-Recognition Modalities with Incomplete Data Sets. MCS Maxim Panov, Alexander Tatarchuk, Vadim Mottl, David Windridge