HPC Resources of the Higher School of Economics
P. S. Kostenetskiy,Roman Chulkevich,V. I. Kozyrev +2 more
- Vol. 1740, Iss: 1, pp 012050
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TLDR
The HPC cluster uses to solve machine learning problems, population genomics, hydrodynamics, atomistic and continuous modeling in physics, generative probabilistic models, financial row forecasting algorithms, and other actual problems.Abstract:
The National Research University Higher School of Economics launched its HPC cluster and created a new division named the Supercomputer Simulation Unit. Now the university HPC cluster occupies seventh place in rating the most powerful computers of the CIS TOP50. The HPC cluster uses to solve machine learning problems, population genomics, hydrodynamics, atomistic and continuous modeling in physics, generative probabilistic models, financial row forecasting algorithms, and other actual problems. Paper describes the HSE HPC resources and experience of their use for scientific and educational tasks.read more
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NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing
TL;DR: In this paper , the authors provided search space of recurrent neural networks on the text datasets and trained 14k architectures within it; they conducted both intrinsic and extrinsic evaluation of the trained models using datasets for semantic relatedness and language understanding evaluation; finally, they have tested several NAS algorithms to demonstrate how the precomputed results can be utilized.
Proceedings Article
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned
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TL;DR: The third edition of the MineRL ObtainDiamond competition, MineRL Diamond 2021, with a separate track in which they permitted any solution to promote the participation of newcomers is described in this paper .
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Atomistic simulations of ettringite and its aqueous interfaces: Structure and properties revisited with the modified ClayFF force field
TL;DR: In this paper , a modified version of the widely used ClayFF force field, ClayFF-MOH, is proposed to explicitly take into account the bending of M-O-H angles of (M = Al, Ca), leading to a much better agreement of the simulation results with available experimental data.
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Properties of aqueous 1,4-dioxane solution via molecular dynamics.
Ivan Bakulin,Ivan Bakulin,Nikolay Kondratyuk,Nikolay Kondratyuk,Nikolay Kondratyuk,Alexander Lankin,Alexander Lankin,Genri E. Norman,Genri E. Norman,Genri E. Norman +9 more
TL;DR: In this paper, the authors performed molecular dynamics calculations of the physical properties of the aqueous 1,4-dioxane solution (density, enthalpy of mixing, and viscosity) and compared them to the available experimental data.
Journal ArticleDOI
Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian
T. V. Shamardina,Vladislav Mikhailov,Daniil Chernianskii,Alena Fenogenova,Marat Saidov,A. Valeeva,Tatiana Shavrina,I. M. Smurov,Elena Tutubalina,Ekaterina Artemova +9 more
TL;DR: This work presents the shared task on artificial text detection in Russian, which is organized as a part of the Dialogue Evaluation initiative, held in 2022, and provides count-based and BERT-based baselines, along with the human evaluation on the first sub-task.
References
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