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09/21/2023
A Comprehensive Review on Financial Explainable AI
The success of artificial intelligence (AI), and deep learning models in...
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09/21/2023
Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package
We propose a parallel (distributed) version of the spectral proper ortho...
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03/05/2023
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis
This paper presents a novel approach for explainability in financial ana...
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12/20/2022
Non-intrusive reduced order models for the accurate prediction of bifurcating phenomena in compressible fluid dynamics
The present works is focused on studying bifurcating solutions in compre...
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02/11/2022
InterpretTime: a new approach for the systematic evaluation of neural-network interpretability in time series classification
We present a novel approach to evaluate the performance of interpretabil...
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01/14/2022
Reduced order modeling for spectral element methods: current developments in Nektar++ and further perspectives
In this paper, we present recent efforts to develop reduced order modeli...
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11/27/2021
Fully-discrete spatial eigenanalysis of discontinuous spectral element methods: insights into well-resolved and under-resolved vortical flows
This study presents a comprehensive spatial eigenanalysis of fully-discr...
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10/18/2021
Neural-network learning of SPOD latent dynamics
We aim to reconstruct the latent space dynamics of high dimensional syst...
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08/19/2021
PyParSVD: A streaming, distributed and randomized singular-value-decomposition library
We introduce PyParSVD[https://github.com/Romit-Maulik/PyParSVD], a Pytho...
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09/18/2020
Industry-Relevant Implicit Large-Eddy Simulation of a High-Performance Road Car via Spectral/hp Element Methods
We present a successful deployment of high-fidelity Large-Eddy Simulatio...
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08/16/2019
Batch 1: Definition of several Weather & Climate Dwarfs
This document is one of the deliverable reports created for the ESCAPE p...
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06/08/2019