A genetic algorithm for autonomous navigation in partially observable domain. - Maxim Borisyak; Andrey Ustyuzhanin (CoRR, 2015)

Application of Kullback-Leibler divergence for short-term user interest detection. - Maxim Borisyak; Roman Zykov; Artem Noskov (CoRR, 2015)

Muon Trigger for Mobile Phones. - Maxim Borisyak; Michail Usvyatsov; Michael Mulhearn; Chase Shimmin; Andrey Ustyuzhanin (CoRR, 2017)

Towards automation of data quality system for CERN CMS experiment. - Maxim Borisyak; Fedor Ratnikov; Denis Derkach; Andrey Ustyuzhanin (CoRR, 2017)

Numerical optimization for Artificial Retina Algorithm. - Maxim Borisyak; Andrey Ustyuzhanin; Denis Derkach; Mikhail Belous (CoRR, 2017)

Deep learning for inferring cause of data anomalies. - V. Azzolini; Maxim Borisyak; Gianluca Cerminara; Denis Derkach; Giovanni Franzoni; F. De Guio; O. Koval; Maurizio Pierini; Adrian Alan Pol; Fedor Ratnikov; Filip Siroky; Andrey Ustyuzhanin; et al. (CoRR, 2017)

Machine Learning on data with sPlot background subtraction. - Maxim Borisyak; Nikita Kazeev (CoRR, 2019)

$(1 + varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets. - Maxim Borisyak; Artem Ryzhikov; Andrey Ustyuzhanin; Denis Derkach; Fedor Ratnikov; Olga Mineeva (CoRR, 2019)

Machine Learning on sWeighted Data. - Maxim Borisyak; Nikita Kazeev (CoRR, 2019)

Normalizing flows for deep anomaly detection. - Artem Ryzhikov; Maxim Borisyak; Andrey Ustyuzhanin; Denis Derkach (CoRR, 2019)

(1 + epsilon)-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets. - Maxim Borisyak; Artem Ryzhikov; Andrey Ustyuzhanin; Denis Derkach; Fedor Ratnikov; Olga Mineeva (J. Mach. Learn. Res., 2020)

Adaptive divergence for rapid adversarial optimization. - Maxim Borisyak; Tatiana Gaintseva; Andrey Ustyuzhanin (PeerJ Comput. Sci., 2020)

NFAD: fixing anomaly detection using normalizing flows. - Artem Ryzhikov; Maxim Borisyak; Andrey Ustyuzhanin; Denis Derkach (PeerJ Comput. Sci., 2021)

When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development. - Nghia Duong-Trung; Stefan Born; Jong Woo Kim; Marie-Therese Schermeyer; Katharina Paulick; Maxim Borisyak; Ernesto C. Martínez; Mariano Nicolás Cruz Bournazou; Thorben Werner; Randolf Scholz; Lars Schmidt-Thieme; Peter Neubauer (CoRR, 2022)

Deep Set Neural Networks for forecasting asynchronous bioprocess timeseries. - Maxim Borisyak; Stefan Born; Peter Neubauer; Mariano Nicolás Cruz Bournazou (CoRR, 2023)

Deep Learning for Fast Inference of Mechanistic Models' Parameters. - Maxim Borisyak; Stefan Born; Peter Neubauer; Mariano Nicolás Cruz Bournazou (CoRR, 2023)

A workflow management system for reproducible and interoperable high-throughput self-driving experiments. - Federico Mione; Lucas Kaspersetz; Martin F. Luna; Judit Aizpuru; Randolf Scholz; Maxim Borisyak; Annina Karolin Kemmer; Marie-Therese Schermeyer; Ernesto C. Martínez; Peter Neubauer; Mariano Nicolás Cruz Bournazou (Comput. Chem. Eng., 2024)

Data Augmentation Scheme for Raman Spectra with Highly Correlated Annotations. - Christoph Lange 007; Isabel Thiele; Lara Santolin; Sebastian L. Riedel; Maxim Borisyak; Peter Neubauer; Mariano Nicolás Cruz Bournazou (CoRR, 2024)