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Andrey Kuzmin
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2020 – today
- 2024
- [i9]Mart van Baalen, Andrey Kuzmin, Markus Nagel, Peter Couperus, Cédric Bastoul, Eric Mahurin, Tijmen Blankevoort, Paul N. Whatmough:
GPTVQ: The Blessing of Dimensionality for LLM Quantization. CoRR abs/2402.15319 (2024) - 2023
- [c17]Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort:
Pruning vs Quantization: Which is Better? NeurIPS 2023 - [i8]Mart van Baalen, Andrey Kuzmin, Suparna S. Nair, Yuwei Ren, Eric Mahurin, Chirag Patel, Sundar Subramanian, Sanghyuk Lee, Markus Nagel, Joseph Soriaga, Tijmen Blankevoort:
FP8 versus INT8 for efficient deep learning inference. CoRR abs/2303.17951 (2023) - [i7]Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort:
Pruning vs Quantization: Which is Better? CoRR abs/2307.02973 (2023) - 2022
- [c16]Mart van Baalen, Brian Kahne, Eric Mahurin, Andrey Kuzmin, Andrii Skliar, Markus Nagel, Tijmen Blankevoort:
Simulated Quantization, Real Power Savings. CVPR Workshops 2022: 2756-2760 - [c15]Suraj Srinivas, Andrey Kuzmin, Markus Nagel, Mart van Baalen, Andrii Skliar, Tijmen Blankevoort:
Cyclical Pruning for Sparse Neural Networks. CVPR Workshops 2022: 2761-2770 - [c14]Andrey Kuzmin, Mart van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, Tijmen Blankevoort:
FP8 Quantization: The Power of the Exponent. NeurIPS 2022 - [i6]Suraj Srinivas, Andrey Kuzmin, Markus Nagel, Mart van Baalen, Andrii Skliar, Tijmen Blankevoort:
Cyclical Pruning for Sparse Neural Networks. CoRR abs/2202.01290 (2022) - [i5]Andrey Kuzmin, Mart van Baalen, Markus Nagel, Arash Behboodi:
Quantized Sparse Weight Decomposition for Neural Network Compression. CoRR abs/2207.11048 (2022) - [i4]Andrey Kuzmin, Mart van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, Tijmen Blankevoort:
FP8 Quantization: The Power of the Exponent. CoRR abs/2208.09225 (2022) - 2020
- [c13]Maxim Safronov, Andrey Kuzmin, Oleg N. Bodin, Viktor Baranov, Olga Timokhina, Oleg Cheban:
Reducing of Bioimpedance Influence on ECG by Correction Filter in Mobile Heart Monitoring System. FRUCT 2020: 200-206
2010 – 2019
- 2019
- [j3]Alan Alimuradov, Alexander Tychkov
, Andrey Kuzmin, Pyotr Churakov, Alexey Ageykin
, Galina Vishnevskaya:
Improved CEEMDAN Based Speech Signal Analysis Algorithm for Mental Disorders Diagnostic System: Pitch Frequency Detection and Measurement. Int. J. Embed. Real Time Commun. Syst. 10(1): 22-47 (2019) - [c12]Maxim Safronov, Andrey Kuzmin, Oleg N. Bodin, Viktor Baranov
, Alexey Trofimov
, Alexander Tychkov
:
Mobile ECG Monitoring Device with Bioimpedance Measurement and Analysis. FRUCT 2019: 375-380 - [i3]Andrey Kuzmin, Markus Nagel, Saurabh Pitre, Sandeep Pendyam, Tijmen Blankevoort, Max Welling:
Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks. CoRR abs/1912.09802 (2019) - 2018
- [j2]Alexander Vakhitov
, Andrey Kuzmin, Victor S. Lempitsky:
Set2Model networks: Learning discriminatively to learn generative models. Comput. Vis. Image Underst. 173: 13-23 (2018) - [c11]Alexander Tychkov
, Andrey Kuzmin, Alan Alimuradov, Alexey Ageykin
, Vladimir Kalistratov, Svetlana Mitroshina:
HHT-based Analysis of ECG Signals of Patients with Borderline Mental Disorders. FRUCT 2018: 257-262 - 2017
- [c10]Alan Alimuradov, Alexander Tychkov
, Andrey Kuzmin
, Pyotr Churakov, Alexey Ageykin
, Galina Vishnevskaya:
Measurement of speech signal patterns under borderline mental disorders. FRUCT 2017: 26-33 - [c9]Andrey Kuzmin, Maxim Safronov, Oleg N. Bodin, Sergey Prokhorov, Anastasya Stolbova
:
Mobile ECG monitoring system prototype and wavelet-based arrhythmia detection. FRUCT 2017: 210-216 - [c8]Maxim Mitrokhin
, Andrey Kuzmin
, Nikita Dyatlov
, Fagim Rakhmatullov, Natalia Mitrokhina, Alan Alimuradov, Alexander Tychkov
:
Investigation of models for prognosis of critical values of non-invasive electrophysiological parameters of pregnant women with abnormalities of heart rate. FRUCT 2017: 238-243 - [c7]Andrey Kuzmin, Alexander Vakhitov
, Victor S. Lempitsky:
Set2Model Networks: Learning Discriminatively To Learn Generative Models. ICCV Workshops 2017: 357-366 - [c6]Andrey Kuzmin, Dmitry Mikushin, Victor S. Lempitsky:
End-to-End learning of cost-volume aggregation for real-time dense stereo. MLSP 2017: 1-6 - 2016
- [j1]Andrey Kuzmin
, Maxim Safronov, Oleg N. Bodin
, Mikhail Petrovsky, Anton Sergeenkov:
Mobile Heart Monitoring System Prototype Based on the Texas Instruments Hardware: Energy Efficiency and J-point Detection. Int. J. Embed. Real Time Commun. Syst. 7(1): 64-84 (2016) - [c5]Anton Ivaschenko, Nikolay Gorbachenko, Alexandr Kolsanov, Andrey Kuzmin
:
Surgery scene representation in 3D simulation training SDK. FRUCT 2016: 75-84 - [c4]Andrey Kuzmin
, Maxim Safronov, Oleg N. Bodin
, Mikhail Petrovsky, Anton Sergeenkov:
Device and software for mobile heart monitoring. FRUCT 2016: 121-127 - [c3]Andrey Kuzmin, Xiang Zhang, Jonathan Fincke, Micha Feigin, Brian W. Anthony, Victor S. Lempitsky:
Fast low-cost single element ultrasound reflectivity tomography using angular distribution analysis. ISBI 2016: 1021-1024 - [i2]Andrey Kuzmin, Dmitry Mikushin, Victor S. Lempitsky:
End-to-end Learning of Cost-Volume Aggregation for Real-time Dense Stereo. CoRR abs/1611.05689 (2016) - [i1]Alexander Vakhitov, Andrey Kuzmin, Victor S. Lempitsky:
Internet-Based Image Retrieval Using End-to-End Trained Deep Distributions. CoRR abs/1612.07697 (2016) - 2015
- [c2]Xiang Zhang, Jonathan Fincke, Andrey Kuzmin, Victor S. Lempitsky, Brian W. Anthony:
A single element 3D ultrasound tomography system. EMBC 2015: 5541-5544 - 2013
- [c1]Andrey Kuzmin, Mathieu Luisier, Olaf Schenk
:
Fast Methods for Computing Selected Elements of the Green's Function in Massively Parallel Nanoelectronic Device Simulations. Euro-Par 2013: 533-544
Coauthor Index
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last updated on 2024-04-24 23:21 CEST by the dblp team
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