25 papers · ranked by Valyu relevance
Zefeng Chen, Wensheng Gan, Jiayang Wu, Kaixia Hu + 1 more
The prevalence of online content has led to the widespread adoption of recommendation systems (RSs), which serve diverse purposes such as news, advertisements, and e-commerce recommendations. Despite their significance, data scarcity issues have significantly impaired the effectiveness of existing RS models and…
Jie Zhang, Dandan Peng
Accurate Remaining Useful Life (RUL) prediction for Lithium-ion batteries is critical for system safety, yet its efficacy is frequently limited by data scarcity in industrial contexts. The robustness of hybrid architectures combining Convolutional Neural Networks (CNNs) with sequential models, a potential solution, has…
Gunther Eysenbach, Nan Zhao, Colin Fincham, Lu Guan + 2 more
Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health…
Nengneng Yu, Yuefan Wang, Lindsey Kathleen Olsen, Bing Zhang + 2 more
Machine learning applications in biomedicine such as omics data analysis are frequently hindered by datasets that are small, high-dimensional, and affected by batch effects across different patient cohorts. To address these challenges, we introduce TabSyM, a modular generative pipeline that synthesizes high-quality…
Nima Nouri
Integrating single-cell RNA sequencing (scRNA-seq) with artificial intelligence (AI) ushers in a new frontier for advanced therapeutic discoveries. However, for this synergy to achieve its full potential, extensive datasets are required to effectively train the AI component. This demand is particularly challenging when…
Kan Hatakeyama-Sato, Seigo Watanabe, Naoki Yamane, Yasuhiko Igarashi + 1 more
Materials informatics and cheminformatics struggle with data scarcity, hindering the extraction of significant relationships between structures and properties. The "Ugly Duckling" theorem, suggesting the difficulty of data processing without assumptions or prior knowledge, exacerbates this problem. Current…
Nadezhda Purtova, Gijs van Maanen
This paper provides a systematic and critical review of the economics literature on data as an economic good and draws lessons for data governance. We conclude that focusing on data as an economic good in governance efforts is hardwired to only result in more data production and cannot deliver other societal goals…
A. E. Hughes, H. R. Statham, A. D. F. Clarke
Previous studies have investigated the effect of target prevalence in combination with the effect of explicit target value on human visual foraging strategies, though the conclusions have been mixed. Some find that individuals have a bias towards high-value targets even when these targets are scarcer, while other…
Haoye Sun, Thorsten Teichert
Scarcity refers to not having enough of what one needs. This phenomenon has shaped individuals´ life since ancient times, nowadays ranging from daily-life scarcity cues in shopping scenarios to the planet’s resources scarcity to meet the world´s consumer demand. Because of this ubiquity of scarcity, the topic has been…
Daniel Choi, Cordelia Yip, Andrew Choi, Junho Park
Synthetic augmentation can silently harm subject-disjoint EEG generalization. We propose trustgated augmentation (TGA), a control layer that scores synthetic windows with a teacher trained on real data for label consistency and confidence; only samples above a confidence quantile q are eligible. A fail-closed selector…
Federico Ottomano, Giovanni De Felice, Vladimir Gusev, Taylor Sparks
Recent Machine Learning (ML) developments have opened new perspectives on accelerating the discovery of new materials. However, in the field of materials informatics, the performance of ML estimators is heavily limited by the nature of the available training datasets, which are often severely restricted and unbalanced.…
Charlotte Christensen, Kennedy Sikenykeny, Damien R. Farine
Behavioural flexibility is considered key for species to cope with the effects of climate change. Periods of resource scarcity, such as during climate change-driven droughts, may force animals to increase their foraging activity to meet energetic demands. However, doing so may increase the thermal risk inherent to the…
Zahr K. Said
In this chapter, I use methods drawn from literary analysis to bear on artificial scarcity and explore how literary and legal storytelling engages in scarcity mongering. I find three particular narrative strategies calculated to compel a conclusion in favor of propertization: the spectacle of need, the diversionary…
Michael J. Madison, Brett M. Frischmann, Madelyn R. Sanfilippo, Katherine J. Strandburg
The economics of abundance, along with the sociology of abundance, the law of abundance, and so forth, should be re-framed, linked, and situated in a common context for empirical rather than conceptual research. Abundance may seem to be a new, big thing, between anxiety over information overload, Big Data, and related…
Longbing Cao
—Data science is creating very exciting trends as well as significant controversy. A critical matter for the healthy development of data science in its early stages is to deeply understand the nature of data and data science, and to discuss the various pitfalls. These important issues motivate the discussions in this…
Victor H. R. Nogueira, Rishabh Sharma, Rafael V. C. Guido, Michael J. Keiser
As efforts to improve the robustness of molecular representations advance, so does the need for methods to test and validate them. We use a Variational Auto-Encoder (VAE), an unsupervised deep learning model, to generate anomalous samples of a well-known molecular string format called SELF-referencIng Embedded Strings…
Authors not listed
The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the ‘FAIR Guiding Principles for scientific data management and stewardship’ provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Hasan M Sayeed, Trupti Mohanty, Taylor Sparks
Recent advancements in large language models (LLMs) have paved the way for automated information extraction in the materials science domain. However, fine-tuning these models, crucial for effective machine learning pipelines in materials science, is hindered by a lack of pre-annotated data. Manual annotation, a…
Shubha Ghosh
Scarcity abounds in law just as abundance is subject to law's limitations. This Article builds on legal theory, economics, and social psychology to present the dialectic of scarcity and abundance as they interplay in our relationship to information and time. This Article has made two overarching arguments: one about…
Claudio Gutiérrez
The foundations of experience (since we absolutely must get down to this) have been non-existent or very weak; nor has a collection or store of particulars yet been sought or made, able or in any way adequate, either in number, kind or certainty, to inform the intellect. [...] Natural history contains nothing that has…
Matthias Scheffler
Matthias Scheffler 1 , Stefan Bauer 2 , Peter Benner 3 , Tristan Bereau 4 , Volker Blum 5 , Mario Boley 6 , Christian Carbogno 7 , C. Richard A. Catlow 8 , Gerhard Dehm 9 , Sebastian Eibl 10 , Ralph Ernstorfer 11 , Ádám Fekete 12 , Lucas Foppa 1 , Peter Fratzl 13 , Christoph Freysoldt 9 , Baptiste Gault 9 , Luca M.…
W. Anderson, R. Apweiler, A. Bateman, G.A. Bauer + 27 more
On November 18-19, 2016, the Human Frontier Science Program Organization (HFSPO) hosted a meeting of senior managers of key data resources and leaders of several major funding organizations to discuss the challenges associated with sustaining biological and biomedical (i.e., life sciences) data resources and associated…
Authors not listed
The nanosafety domain has seen significant advancements in data generation and sharing, yet challenges remain in ensuring data interoperability and reuse. This article focuses on developing a semantic interoperability framework for nanosafety data to maximize the FAIRness (Findability, Accessibility, Interoperability…
M. TAMER ÖZSU
Work-in-progressThere has been an increasing recognition of the value of data and of data-based decision making. As a consequence, the development of data science as a field of study has intensified in recent years. However, there is no systematic and comprehensive treatment and understanding of data science. This…