Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs. - Denis Mazur; Vage Egiazarian; Stanislav Morozov; Artem Babenko (NeurIPS, 2019)

Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs. - Denis Mazur; Vage Egiazarian; Stanislav Morozov; Artem Babenko (CoRR, 2019)

Distributed Deep Learning In Open Collaborations. - Michael Diskin; Alexey Bukhtiyarov; Max Ryabinin; Lucile Saulnier; Quentin Lhoest; Anton Sinitsin; Dmitry Popov 003; Dmitry V. Pyrkin; Maxim Kashirin; Alexander Borzunov; Albert Villanova del Moral; Denis Mazur; et al. (NeurIPS, 2021)

Fast Inference of Mixture-of-Experts Language Models with Offloading. - Artyom Eliseev; Denis Mazur (CoRR, 2023)

TQCompressor: Improving Tensor Decomposition Methods in Neural Networks Via Permutations. - Vadim Abronin; Aleksei Naumov; Denis Mazur; Dmitriy Bystrov; Katerina Tsarova; Artem Melnikov; Sergey Dolgov; Reuben Brasher; Michael Perelshtein (MIPR, 2024)

PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression. - Vladimir Malinovskii; Denis Mazur; Ivan Ilin; Denis Kuznedelev; Konstantin Burlachenko; Kai Yi; Dan Alistarh; Peter Richtárik (NeurIPS, 2024)

TQCompressor: improving tensor decomposition methods in neural networks via permutations. - Vadim Abronin; Aleksei Naumov; Denis Mazur; Dmitriy Bystrov; Katerina Tsarova; Artem Melnikov; Ivan V. Oseledets; Sergey Dolgov; Reuben Brasher; Michael Perelshtein (CoRR, 2024)

Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models. - Alina Shutova; Vladimir Malinovskii; Vage Egiazarian; Denis Kuznedelev; Denis Mazur; Nikita Surkov; Ivan Ermakov; Dan Alistarh (CoRR, 2025)