Results 61 to 70 of about 36,247 (313)
IEEE Access, 2022 There have existed many studies about the explainable artificial intelligence (XAI) that explains the logic behind the complex deep neural network called a black box.
Junhee Lee +4 more
doaj +1 more source
FEBS Letters, EarlyView.We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley +1 more source
IEEE Access, 2023 Learning with graph-structured data, such as social, biological, and financial networks, requires effective low-dimensional representations to handle their large and complex interactions.
Hogun Park
doaj +1 more source
FEBS Letters, EarlyView.Structural and biochemical characterisations show that the planar cell polarity (PCP) protein Inturned harbours a unique PDZ‐like domain that does not bind canonical PDZ‐binding motifs (PBMs) like that of another PCP protein Vangl2. In contrast, the apical‐basal polarity protein Scribble contains four PDZ domains that bind Vangl2, but one PDZ domain ...
Stephan Wilmes +4 more
wiley +1 more source
Explainability in Music Recommender System [PDF]
Recommendation systems play a crucial role in our daily lives, influencing many of our significant and minor decisions. These systems also have become integral to the music industry, guiding users to discover new content based on their tastes.
Shashaani, Shahrzad; orcid:
core +1 more source
Explainability-driven adversarial robustness assessment for generalized deepfake detectors
EURASIP Journal on Information SecurityThe capabilities of generative models to produce high-quality fake images require deepfake detectors to be accurate and have strong generalization performance.
Lorenzo Cirillo +2 more
doaj +1 more source
BubblEX: An Explainable Deep Learning Framework for Point-Cloud Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Point-cloud data are nowadays one of the major data sources for describing our environment. Recently, deep architectures have been proposed as a key step in understanding and retrieving semantic information.
Francesca Matrone +4 more
doaj +1 more source
Calpain small subunit homodimerization is robust and calcium‐independent
FEBS Letters, EarlyView.Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy +4 more
wiley +1 more source
Reimagining explainability in expert contexts: setting foundations for effective expert-AI interactions through design and collaboration [PDF]
Domain experts increasingly rely on Artificial Intelligence (AI) systems to support their decision-making. However, they often struggle to build meaningful trust in opaque and complex technologies or find them poorly fitting within their workflows.
Simkute, Auste
core +1 more source
Quantifying the Demand for Explainability
, 2021 Part 9: Explainable AIInternational audienceSoftware that uses Artificial Intelligence technology like Machine Learning is becoming ubiquitous with even more applications ahead.
Hußmann, Heinrich +5 more
core +1 more source