Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms. - Attila Lovas; Iosif Lytras; Miklós Rásonyi; Sotirios Sabanis (CoRR, 2020)

Taming under isoperimetry. - Iosif Lytras; Sotirios Sabanis (CoRR, 2023)

Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms. - Attila Lovas; Iosif Lytras; Miklós Rásonyi; Sotirios Sabanis (SIAM J. Math. Data Sci., 2023)

Kinetic Langevin MCMC sampling without gradient Lipschitz continuity - the strongly convex case. - Tim Johnston; Iosif Lytras; Sotirios Sabanis (J. Complex., 2024)

Tamed Langevin sampling under weaker conditions. - Iosif Lytras; Panayotis Mertikopoulos (AISTATS, 2025)

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients. - Iosif Lytras; Sotirios Sabanis; Ying Zhang 037 (CoRR, 2025)