Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks. - Maxim Kodryan; Artem M. Grachev; Dmitry I. Ignatov; Dmitry P. Vetrov (RepL4NLP@ACL, 2019)

On Power Laws in Deep Ensembles. - Ekaterina Lobacheva; Nadezhda Chirkova; Maxim Kodryan; Dmitry P. Vetrov (NeurIPS, 2020)

On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. - Ekaterina Lobacheva; Maxim Kodryan; Nadezhda Chirkova; Andrey Malinin; Dmitry P. Vetrov (NeurIPS, 2021)

Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes. - Maxim Kodryan; Ekaterina Lobacheva; Maksim Nakhodnov; Dmitry P. Vetrov (NeurIPS, 2022)

MARS: Masked Automatic Ranks Selection in Tensor Decompositions. - Maxim Kodryan; Dmitry Kropotov; Dmitry P. Vetrov (AISTATS, 2023)

Large Learning Rates Improve Generalization: But How Large Are We Talking About? - Ekaterina Lobacheva; Eduard Pockonechnyy; Maxim Kodryan; Dmitry P. Vetrov (CoRR, 2023)

Where Do Large Learning Rates Lead Us? - Ildus Sadrtdinov; Maxim Kodryan; Eduard Pokonechny; Ekaterina Lobacheva; Dmitry P. Vetrov (NeurIPS, 2024)