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Semantic tensor networks for large data sets analysis [1]

Project funded by Narodowe Centrum Nauki (OPUS 8) Number: 2014/15/B/ST6/05204

Numer projektu: 

2014/15/B/ST6/05204

Termin: 

30/09/2015 to 29/03/2019

Typ projektu: 

Projekt własny badawczy

Wykonawcy projektu: 

Krzysztof Domino, PhD [2]
Łukasz Pawela, PhD [3]
Zbigniew Puchała, prof. [4]
Jarosław Miszczak, PhD [5]
Michał Romaszewski, PhD [6]

Kierownik zespołu / promotor: 

Piotr Gawron [7]

Publications: 

The use of the multi-cumulant tensor analysis for the algorithmic optimisation of investment portfolios [8]
Quantum hidden Markov models based on transition operation matrices [9]
Properties of quantum stochastic walks from the asymptotic scaling exponent [10]
Efficient computation of higher order cumulant tensors [11]
An algorithm for arbitrary–order cumulant tensor calculation in a sliding window of data streams [12]
Superdiffusive quantum stochastic walk definable on arbitrary directed graph [13]
Unified approach to geometric and positive-map-based non-linear entanglement identifiers [14]
Introducing higher order correlations to marginals' subset of multivariate data by means of Archimedean copulas [15]
Approximation of quantum control correction scheme using deep neural networks [16]
Impact of global and local interaction on quantum spatial search on chimera graph [17]
QuantumInformation.jl—a Julia package for numerical computation in quantum information theory [18]
Multivariate cumulants in outlier detection for financial data analysis [19]
An application of higher order multivariate cumulants in modelling of myoelectrical activity of porcine uterus during early pregnancy [20]

Links
[1] https://iscis2016.iitis.pl/en/project/semantic-tensor-networks-large-data-sets-analysis [2] https://iscis2016.iitis.pl/person/kdomino [3] https://iscis2016.iitis.pl/person/lpawela [4] https://iscis2016.iitis.pl/person/zpuchala [5] https://iscis2016.iitis.pl/person/jmiszczak [6] https://iscis2016.iitis.pl/person/mromaszewski [7] https://iscis2016.iitis.pl/person/pgawron [8] https://iscis2016.iitis.pl/en/content/use-multi-cumulant-tensor-analysis-algorithmic-optimisation-investment-portfolios [9] https://iscis2016.iitis.pl/en/content/quantum-hidden-markov-models-based-transition-operation-matrices [10] https://iscis2016.iitis.pl/en/content/properties-quantum-stochastic-walks-asymptotic-scaling-exponent [11] https://iscis2016.iitis.pl/en/content/efficient-computation-higher-order-cumulant-tensors [12] https://iscis2016.iitis.pl/en/content/algorithm-arbitrary%E2%80%93order-cumulant-tensor-calculation-sliding-window-data-streams [13] https://iscis2016.iitis.pl/en/content/superdiffusive-quantum-stochastic-walk-definable-arbitrary-directed-graph [14] https://iscis2016.iitis.pl/en/content/unified-approach-geometric-and-positive-map-based-non-linear-entanglement-identifiers [15] https://iscis2016.iitis.pl/en/content/introducing-higher-order-correlations-marginals-subset-multivariate-data-means-archimedean [16] https://iscis2016.iitis.pl/en/content/approximation-quantum-control-correction-scheme-using-deep-neural-networks [17] https://iscis2016.iitis.pl/en/content/impact-global-and-local-interaction-quantum-spatial-search-chimera-graph [18] https://iscis2016.iitis.pl/en/content/quantuminformationjl%E2%80%94-julia-package-numerical-computation-quantum-information-theory [19] https://iscis2016.iitis.pl/en/content/multivariate-cumulants-outlier-detection-financial-data-analysis [20] https://iscis2016.iitis.pl/en/content/application-higher-order-multivariate-cumulants-modelling-myoelectrical-activity-porcine