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Agnieszka Niemczynowicz

4 papers hereh-index 343 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.NE1
  • econ.TH1
same name
  • Agnieszka Niemczynowicz — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedHypercomplex neural network in time series forecasting of stock data

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

econ.TH2026

Diffusion of tacit knowledge in a company: a mathematical model based on diffusion on graphs

Radosław A. Kycia, Agnieszka Niemczynowicz, Andrzej Buszko

This article is devoted to the process of diffusing tacit knowledge. This intangible asset has proven crucial for achieving a competitive advantage among market-oriented companies.…

cs.LG2024

Fully tensorial approach to hypercomplex-valued neural networks

Agnieszka Niemczynowicz, Radosław Antoni Kycia

A fully tensorial theoretical framework for hypercomplex-valued neural networks is presented. The proposed approach enables neural network architectures to operate on data defined…

cs.LG2024

KHNNs: hypercomplex neural networks computations via Keras using TensorFlow and PyTorch

Agnieszka Niemczynowicz, Radosław Antoni Kycia

Neural networks used in computations with more advanced algebras than real numbers perform better in some applications. However, there is no general framework for constructing hype…

cs.NE2024★ 1 cited

Hypercomplex neural network in time series forecasting of stock data

Radosław Kycia, Agnieszka Niemczynowicz

The goal of this paper is to test three classes of neural network (NN) architectures based on four-dimensional (4D) hypercomplex algebras for time series prediction. We evaluate di…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.