Nonparametric System identification of Stochastic Switched Linear Systems by Sarkar, Tuhin, Rakhlin, Alexander, Dahleh, Munther A

“…This is achieved by constructing Hankel-like matrices from data and obtaining suitable approximations via SVD truncation where the threshold for SVD truncation is purely data dependent. By exploiting tools from theory of model reduction for SLS, we find that the system parameter estimates are close to a balanced truncated realization of the underlying system with high probability.…”
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Improving air quality assessment using physics-inspired deep graph learning by Lianfa Li, Jinfeng Wang, Meredith Franklin, Qian Yin, Jiajie Wu, Gustau Camps-Valls, Zhiping Zhu, Chengyi Wang, Yong Ge, Markus Reichstein

“…Abstract Existing methods for fine-scale air quality assessment have significant gaps in their reliability. Purely data-driven methods lack any physically-based mechanisms to simulate the interactive process of air pollution, potentially leading to physically inconsistent or implausible results. …”
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Deep learning-based automated building construction progress monitoring for prefabricated prefinished volumetric construction by Chua, Wei Png

“…Therefore, it is hard to apply existing purely data-driven object detectors to automate building progress monitoring at construction sites. …”
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Why We Can't Help but Call Ourselves (All) ‘Sartorians’ by Marco Giuliani

“…The text highlights Sartori’s insistence on theory-driven approaches over purely data-centred methods, as well as his critical stance on the behavioural drift of social sciences. …”
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A Matlab Toolbox for Extended Dynamic Mode Decomposition Based on Orthogonal Polynomials and p-q Quasi-Norm Order Reduction by Camilo Garcia-Tenorio, Alain Vande Wouwer

“…EDMD can operate in a purely data-driven way using either data generated by a numerical simulator of arbitrary complexity or actual experimental data. …”
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Deep-learning-based automated building construction progress monitoring for prefabricated prefinished volumetric construction by Chua, Wei Png, Cheah, Chien Chern

“…Therefore, it is hard to apply existing purely data-driven object detectors to automate building progress monitoring at construction sites. …”
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Forecasting country conflict using statistical learning methods by Sarah Neumann, Darryl Ahner, Raymond R. Hill

“…Research limitations/implications – The study is based on actual historical data and is purely data driven. Practical implications – The study demonstrates the utility of the analytical methodology but carries not implementation recommendations. …”
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Combining physical simulators and object-based networks for control by Ajay, Anurag., Bauza Villalonga, Maria, Wu, Jiajun, Fazeli, Nima, Tenenbaum, Joshua B, Rodriguez Garcia, Alberto, Kaelbling, Leslie P

“…Compared with existing models that are purely analytical or purely data-driven, our hybrid model captures the dynamics of interacting objects in a more accurate and data-efficient manner. …”
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Manifold Learning With Contracting Observers for Data-Driven Time-Series Analysis by Shnitzer, Tal, Talmon, Ronen, Slotine, Jean-Jacques

“…In this paper, we propose a method for building an intrinsic representation of such signals in a purely data-driven manner. First, we apply a manifold learning technique, diffusion maps, to learn the intrinsic model of the latent variables of the dynamical system, solely from the measurements. …”
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Manifold Learning With Contracting Observers for Data-Driven Time-Series Analysis by Shnitzer, Tal, Talmon, Ronen, Slotine, Jean-Jacques E

“…In this paper, we propose a method for building an intrinsic representation of such signals in a purely data-driven manner. First, we apply a manifold learning technique, diffusion maps, to learn the intrinsic model of the latent variables of the dynamical system, solely from the measurements. …”
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Hierarchical attentive recurrent tracking by Kosiorek, A, Bewley, A, Posner, H

“…This framework is fully differentiable and can be trained in a purely data driven fashion by gradient methods. To improve training convergence, we augment the loss function with terms for a number of auxiliary tasks relevant for tracking. …”

To TTP or not to TTP? Exploiting TTPs to improve ML-based malware detection by Sharma, Y, Giunchiglia, E, Birnbach, S, Martinovic, I

“…While these approaches have surely demonstrated their effectiveness, they still present limitations, some of which are a consequence of their purely data-driven nature. In this paper, we show how the MITRE ATT&CK framework of tactics, techniques, and procedures (TTPs) can be exploited to overcome such limitations and improve their ability to detect malware on networks. …”

An explainable AI framework for spatiotemporal risk factor analysis in public health: a case study of cardiovascular mortality in South Korea by Eunjin Kang, Dongjin Cho, Siwoo Lee, Jungho Im, Dongwook Lee, Cheolhee Yoo

“…Compared to previous purely data-driven XAI-based analyses, the proposed schemes achieved significantly better results in capturing regional exposure-response relationships. …”
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A priori physical information to aid generalization capabilities of neural networks for hydraulic modeling by Gianmarco Guglielmo, Andrea Montessori, Jean-Michel Tucny, Michele La Rocca, Pietro Prestininzi

“…Consequently, many purely data-driven Neural Networks have shown limited capabilities when tasked with predicting new scenarios. …”
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Design – a new way to look at old molecules by Spalvieri Davide, Mauviel Anne-Marine, Lambert Matthieu, Férey Nicolas, Sacquin-Mora Sophie, Chavent Matthieu, Baaden Marc

“…By describing the design process of abstracted shapes, exploded views of molecular structures, motion-averaged slices, 360-degree panoramic projections, and experiments with lit sphere shading, we document how designers help make scientific data accessible without betraying its meaning, and how a creative mind adds value over purely data-driven visualizations. A similar conclusion was drawn for public outreach, as we found that comic-book-style drawings are better suited for communicating science to a broad audience.…”
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The Electrical Conductivity of Ionic Liquids: Numerical and Analytical Machine Learning Approaches by Theodoros E. Karakasidis, Filippos Sofos, Christos Tsonos

“…The suggested platform is capable of providing either a fast, numerical prediction mechanism or an analytical expression, both purely data-driven, that can be generalized and exploited in similar property prediction projects, overcoming expensive experimental procedures and computationally intensive molecular simulations.…”
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Statistical analysis of three data sources for Covid-19 monitoring in Rhineland-Palatinate, Germany by Maximilian Pilz, Karl-Heinz Küfer, Jan Mohring, Johanna Münch, Jarosław Wlazło, Neele Leithäuser

“…We observe that this is possible in general for the cohort study prevalence, while the wastewater data suffer from a too large variability to make quantitative predictions by a purely data-driven approach. However, the wastewater data and the cohort study prevalence are able to detect hospitalizations waves in a qualitative manner. …”
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DeepFocus: fast focus and astigmatism correction for electron microscopy by P. J. Schubert, R. Saxena, J. Kornfeld

“…Here, we introduce DeepFocus, a purely data-driven method for aberration correction in scanning electron microscopy. …”
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Data-driven definition and modelling of plant growth by Vijja Wichitwechkarn, William Rohde, Charles Fox, Ruchi Choudhary

“…This work provides a purely data-driven definition, that is easy to train, easy to non-destructively acquire training data, does not require expert annotations, and is easy to compute for any new plant type and growing conditions. …”
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Neurally-guided structure inference by Lu, Sidi, Mao, Jiayuan, Tenenbaum, Joshua B, Wu, Jiajun

“…Most structure inference methods either rely on exhaustive search or are purely data-driven. Exhaustive search robustly infers the structure of arbitrarily complex data, but it is slow. …”
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