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cs.LG2025
Towards Universal Neural Operators through Multiphysics Pretraining
Mikhail Masliaev, Dmitry Gusarov, Ilya Markov +1
Although neural operators are widely used in data-driven physical simulations, their training remains computationally expensive. Recent advances address this issue via downstream l…
cs.LG2023
Towards stable real-world equation discovery with assessing differentiating quality influence
Mikhail Masliaev, Ilya Markov, Alexander Hvatov
This paper explores the critical role of differentiation approaches for data-driven differential equation discovery. Accurate derivatives of the input data are essential for reliab…