add files to bib

Author: dgullate

publications.bib

@@ -20,3 +20,49 @@ @article{gomez2010extension
   publisher={Elsevier}
 }
 
+@article{Butt2022,
+   abstract = {Many recent studies have focused on the automatic classification of electrocardiogram (ECG) signals using deep learning (DL) methods. Most rely on existing complex DL methods, such as transfer learning or providing the models with carefully designed extracted features based on domain knowledge. A common assumption is that the deeper and more complex the DL model is, the better it learns. In this study, we propose two different DL models for automatic feature extraction from ECG signals for classification tasks: A CNN-LSTM hybrid model and an attention/transformer-based model with wavelet transform for the dimensional embedding. Both of the models extract the features from time series at the initial layers of the neural networks and can obtain performance at least equal to, if not greater than, many contemporary deep neural networks. To validate our hypothesis, we used three publicly available data-sets to evaluate the proposed models. Our model achieved a benchmark accuracy of 99.92% for fall detection and 99.93% for the PTB database for myocardial infarction versus normal heartbeat classification.},
+   author = {Fatima Sajid Butt and Matthias F. Wagner and Jörg Schäfer and David Gomez Ullate},
+   doi = {10.1109/ACCESS.2022.3220670},
+   issn = {21693536},
+   journal = {IEEE Access},
+   title = {Toward Automated Feature Extraction for Deep Learning Classification of Electrocardiogram Signals},
+   volume = {10},
+   year = {2022}
+}
+@article{García-Ferrero2019,
+   abstract = {It was recently conjectured that every system of exceptional orthogonal polynomials is related to a classical orthogonal polynomial system by a sequence of Darboux transformations. In this paper we prove this conjecture, which paves the road to a complete classification of all exceptional orthogonal polynomials. In some sense, this paper can be regarded as the extension of Bochner's result for classical orthogonal polynomials to the exceptional class. As a supplementary result, we derive a canonical form for exceptional operators based on a bilinear formalism, and prove that every exceptional operator has trivial monodromy at all primary poles.},
+   author = {MaÁngeles García-Ferrero and David Gómez-Ullate and Robert Milson},
+   doi = {10.1016/j.jmaa.2018.11.042},
+   issn = {10960813},
+   issue = {1},
+   journal = {Journal of Mathematical Analysis and Applications},
+   title = {A Bochner type characterization theorem for exceptional orthogonal polynomials},
+   volume = {472},
+   year = {2019}
+}
+
+
+@article{Precioso2023,
+   abstract = {Non-intrusive load monitoring (NILM) is the problem of predicting the status or consumption of individual domestic appliances only from the knowledge of the aggregated power load. NILM is often formulated as a classification (ON/OFF) problem for each device. However, the training datasets gathered by smart meters do not contain these labels, but only the electric consumption at every time interval. This paper addresses a fundamental methodological problem in how a NILM problem is posed, namely how the different possible thresholding methods lead to different classification problems. Standard datasets and NILM deep learning models are used to illustrate how the choice of thresholding method affects the output results. Some criteria that should be considered for the choice of such methods are also proposed. Finally, we propose a slight modification to current deep learning models for multi-tasking, i.e. tackling the classification and regression problems simultaneously. Transfer learning between both problems might improve performance on each of them.},
+   author = {Daniel Precioso and David Gómez-Ullate},
+   doi = {10.1007/s11227-023-05149-8},
+   issn = {15730484},
+   issue = {13},
+   journal = {Journal of Supercomputing},
+   title = {Thresholding methods in non-intrusive load monitoring},
+   volume = {79},
+   year = {2023}
+}
+@misc{G\'omez-Ullate2010,
+   author = {David Gómez-Ullate and Sara Lombardo and Manuel Mañas and Marta Mazzocco and Frank Nijhoff and Matteo Sommacal},
+   doi = {10.1088/1751-8121/43/43/430301},
+   issn = {17518113},
+   issue = {43},
+   journal = {Journal of Physics A: Mathematical and Theoretical},
+   title = {Integrability and nonlinear phenomena},
+   volume = {43},
+   year = {2010}
+}
+
+