Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data: Extended Abstract. - Valentina Shumovskaia; Kirill Fedyanin; Ivan Sukharev; Dmitry Berestnev; Maxim Panov (DSAA, 2020)

EWS-GCN: Edge Weight-Shared Graph Convolutional Network for Transactional Banking Data. - Ivan Sukharev; Valentina Shumovskaia; Kirill Fedyanin; Maxim Panov; Dmitry Berestnev (ICDM, 2020)

Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampled Implicit Ensembles. - Evgenii Tsymbalov; Kirill Fedyanin; Maxim Panov (CoRR, 2020)

Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling. - Kirill Fedyanin; Evgenii Tsymbalov; Maxim Panov (AIST (Supplement), 2021)

How Certain is Your Transformer? - Artem Shelmanov; Evgenii Tsymbalov; Dmitry Puzyrev; Kirill Fedyanin; Alexander Panchenko; Maxim Panov (EACL, 2021)

Retrospective on the SENSORIUM 2022 competition. - 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; et al. (NeurIPS (Competition and Demos), 2021)

Linking bank clients using graph neural networks powered by rich transactional data. - Valentina Shumovskaia; Kirill Fedyanin; Ivan Sukharev; Dmitry Berestnev; Maxim Panov (Int. J. Data Sci. Anal., 2021)

Uncertainty Estimation of Transformer Predictions for Misclassification Detection. - Artem Vazhentsev; Gleb Kuzmin; Artem Shelmanov; Akim Tsvigun; Evgenii Tsymbalov; Kirill Fedyanin; Maxim Panov; Alexander Panchenko; Gleb Gusev; Mikhail Burtsev 001; Manvel Avetisian; Leonid Zhukov (ACL (1), 2022)

Nonparametric Uncertainty Quantification for Single Deterministic Neural Network. - Nikita Kotelevskii; Aleksandr Artemenkov; Kirill Fedyanin; Fedor Noskov; Alexander Fishkov; Artem Shelmanov; Artem Vazhentsev; Aleksandr Petiushko; Maxim Panov (NeurIPS, 2022)

NUQ: Nonparametric Uncertainty Quantification for Deterministic Neural Networks. - Nikita Kotelevskii; Aleksandr Artemenkov; Kirill Fedyanin; Fedor Noskov; Alexander Fishkov; Aleksandr Petiushko; Maxim Panov (CoRR, 2022)

ScaleFace: Uncertainty-aware Deep Metric Learning. - Roman Kail; Kirill Fedyanin; Nikita Muravev; Alexey Zaytsev 002; Maxim Panov (DSAA, 2023)

LM-Polygraph: Uncertainty Estimation for Language Models. - Ekaterina Fadeeva; Roman Vashurin; Akim Tsvigun; Artem Vazhentsev; Sergey Petrakov; Kirill Fedyanin; Daniil Vasilev; Elizaveta Goncharova; Alexander Panchenko; Maxim Panov; Timothy Baldwin; Artem Shelmanov (EMNLP (Demos), 2023)

One-Step Distributional Reinforcement Learning. - Mastane Achab; Réda Alami; Yasser Abdelaziz Dahou Djilali; Kirill Fedyanin; Eric Moulines (Trans. Mach. Learn. Res., 2023)

Falcon2-11B Technical Report. - Quentin Malartic; Nilabhra Roy Chowdhury; Ruxandra Cojocaru; Mugariya Farooq; Giulia Campesan; Yasser Abdelaziz Dahou Djilali; Sanath Narayan; Ankit Singh; Maksim Velikanov; Basma El Amel Boussaha; Mohammed Al-Yafeai; Hamza Alobeidli; et al. (CoRR, 2024)