Results 71 to 80 of about 36,247 (313)
Applied SciencesPost hoc explanations for black-box machine learning models have been criticized for potentially inaccurate surrogate models and computational burden at prediction time.
Cagla Acun, Olfa Nasraoui
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Proceedings of the National Academy of Sciences, 2003 What do social survey data tell us about the determinants of happiness? First, that the psychologists' setpoint model is questionable. Life events in the nonpecuniary domain, such as marriage, divorce, and serious disability, have a lasting effect on happiness, and do not simply deflect the average person temporarily above or below a setpoint given by ...
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Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
FEBS Letters, EarlyView.A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
Comparative analysis between different explainability techniques.
, 2022 Comparative analysis between different explainability techniques.
Rohan Gorantla (8431053) +3 more
core +1 more source
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Looking at Exploratory Paradigms of Explainability in Creative Computing
The debate on creative computing revolves around two important questions: Can creative artifacts generated by machines be explained and can they be measured and distinguished?
Patnaik, Lalith Mohan, Kulkarni, Parag
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Explainable analysis of infrared and visible light image fusion based on deep learning
Scientific ReportsExplainability is a very active area of research in machine learning and image processing. This paper aims to investigate the explainability of visible light and infrared image fusion technology in order to enhance the credibility of model understanding ...
Bo Yuan +4 more
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Toward Explainable Facial Expression Recognition Using Face Action Units: XFER-AU
IEEE AccessFace expression recognition (FER) has been extensively explored by the research community, with comparisons between different FER models typically relying on accuracy metrics.
Tanmay Tulsidas Verlekar +2 more
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Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
SSRN Electronic Journal, 2010 Statistical modeling is a powerful tool for developing and testing theories by way of causal explanation, prediction, and description. In many disciplines there is near-exclusive use of statistical modeling for causal explanation and the assumption that models with high explanatory power are inherently of high predictive power.
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