Machine learning approach to force reconstruction in photoelastic materials. - Renat Sergazinov; Miroslav Kramár (Mach. Learn. Sci. Technol., 2021)

Gluformer: Transformer-based Personalized glucose Forecasting with uncertainty quantification. - Renat Sergazinov; Mohammadreza Armandpour; Irina Gaynanova (ICASSP, 2023)

SwitchTab: Switched Autoencoders Are Effective Tabular Learners. - Jing Wu; Suiyao Chen; Qi Zhao; Renat Sergazinov; Chen Li; Shengjie Liu; Chongchao Zhao; Tianpei Xie; Hanqing Guo; Cheng Ji 005; Daniel Cociorva; Hakan Brunzell (AAAI, 2024)

GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks. - Renat Sergazinov; Elizabeth Chun; Valeriya Rogovchenko; Nathaniel J. Fernandes; Nicholas Kasman; Irina Gaynanova (ICLR, 2024)

A spectral method for multi-view subspace learning using the product of projections. - Renat Sergazinov; Armeen Taeb; Irina Gaynanova (CoRR, 2024)

Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels. - Renat Sergazinov; Richard Chen; Cheng Ji 005; Jing Wu; Daniel Cociorva; Hakan Brunzell (AAAI, 2025)

Random at First, Fast at Last: NTK-Guided Fourier Pre-Processing for Tabular DL. - Renat Sergazinov; Jing Wu; Shao-An Yin (CoRR, 2025)