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In singular models, the optimal set of parameters forms an analytic set with singularities, and a classical statistical inference cannot be applied to such models. This is significant for deep learning as neural networks are singular, and thus, "dividing" by the determinant of the Hessian or employing the Laplace approximation is not appropriate. Despite its potential for addressing fundamental issues in deep learning, a singular learning theory appears to have made little inroads into the developing canon of a deep learning theory. Via a mix of theory and experiment, we present an invitation to the singular learning theory as a vehicle for understanding deep learning and suggest an important future work to make the singular learning theory directly applicable to how deep learning is performed in practice.
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http://dx.doi.org/10.1109/TNNLS.2022.3167409 | DOI Listing |
Adv Sci (Weinh)
March 2025
State Key Laboratory of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, P. R. China.
Evolutionary constraints significantly limit the diversity of naturally occurring enzymes, thereby reducing the sequence repertoire available for enzyme discovery and engineering. Recent breakthroughs in protein structure prediction and de novo design, powered by artificial intelligence, now enable to create enzymes with desired functions without solely relying on traditional genome mining. Here, a computational strategy is demonstrated for creating new-to-nature polyethylene terephthalate hydrolases (PET hydrolases) by leveraging the known catalytic mechanisms and implementing multiple deep learning algorithms and molecular computations.
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March 2025
School of Nursing, Beijing University of Chinese Medicine, Beijing, China.
Background: Artificial intelligence (AI) has shown immense potential in the field of medicine, but its actual effectiveness and safety still need to be validated through clinical trials. Currently, the research themes, methodologies, and development trends of AI-related clinical trials remain unclear, and further exploration of these studies will be crucial for uncovering AI's practical application potential and promoting its broader adoption in clinical settings.
Objective: To analyze the current status, hotspots, and trends of published clinical research on AI applications.
Physicians evaluate a patient's respiratory health during a physical examination by visual assessment of the work of breathing (WoB) to determine respiratory stability, and by detecting abnormal lung sounds via lung auscultation using a stethoscope to identify common pathological lung diseases, such as chronic obstructive pulmonary disease (COPD) and pneumonia. Since these assessment methods are subjective, a low-profile device used for an accurate and quantitative monitoring approach could provide valuable preemptive insights into respiratory health, proving to be clinically beneficial. To achieve this goal, we have developed a miniature patch consisting of a sensitive wideband multi-axis seismometer that can be placed on the anatomical areas of a patient's lungs to enable an effective quantification of a patient's WoB and lung sounds.
View Article and Find Full Text PDFSci Rep
March 2025
College of Data Science and Application, Inner Mongolia University of Technology, Hohhot, 010080, China.
The rapid increase in carbon emissions from the logistics transportation industry has underscored the urgent need for low-carbon logistics solutions. Electric logistics vehicles (ELVs) are increasingly being considered as replacements for traditional fuel-powered vehicles to reduce emissions in urban logistics. However, ELVs are typically limited by their battery capacity and load constraints.
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March 2025
Centro de Investigación en Computación, Instituto Politécnico Nacional (CIC-PN), 07738, Mexico City, Mexico.
Social media has become a powerful tool for public discourse, shaping opinions and the emotional landscape of communities. The extensive use of social media has led to a massive influx of online content. This content includes instances where negativity is amplified through hateful speech but also a significant number of posts that provide support and encouragement, commonly known as hope speech.
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