Noise Reduction in X-ray Photon Correlation Spectroscopy with Convolutional Neural Networks Encoder-Decoder Models. - Tatiana Konstantinova; Lutz Wiegart; Maksim S. Rakitin; Anthony M. DeGennaro; Andi M. Barbour (CoRR, 2021)

Machine learning enabling high-throughput and remote operations at large-scale user facilities. - Tatiana Konstantinova; Phillip M. Maffettone; Bruce Ravel; Stuart I. Campbell; Andi M. Barbour; Daniel Olds (CoRR, 2022)

Machine Learning Enhances Algorithms for Quantifying Non-Equilibrium Dynamics in Correlation Spectroscopy Experiments to Reach Frame-Rate-Limited Time Resolution. - Tatiana Konstantinova; Lutz Wiegart; Maksim S. Rakitin; Anthony M. DeGennaro; Andi M. Barbour (CoRR, 2022)

Obtaining weights for Gröbner basis computation in parameter identifiability problems. - Mariya Bessonov; Ilia Ilmer; Tatiana Konstantinova; Alexey Ovchinnikov; Gleb Pogudin; Pedro Soto 001 (CoRR, 2022)

Faster Groebner bases for Lie derivatives of ODE systems via monomial orderings. - Mariya Bessonov; Ilia Ilmer; Tatiana Konstantinova; Alexey Ovchinnikov; Gleb Pogudin; Pedro Soto 001 (ISSAC, 2024)