This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
install Install one, more, or all versions from a python-build-standalone release. update (or upgrade) Update one, more, or all versions to another release. remove (or uninstall) Remove/uninstall one, ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
An interactive toolbox for standardizing, validating, simulating, reducing, and exploring detailed biophysical models that can be used to reveal how morpho-electric properties map to dendritic and ...
Official implementation of the paper Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection accepted at the 21st International Conference ...
Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
Abstract: Data distribution shift is a common problem in machine learning-powered smart city applications where the test data differs from the training data. Augmenting smart city applications with ...
The forecasts will offer a glimpse of the path for policy at a highly uncertain moment for economy — and the central bank. By Colby Smith Federal Reserve officials are scheduled to release a fresh set ...
Abstract: The rise of advanced data technologies in electric power distribution systems enables operators to optimize operations but raises concerns about data security and consumer privacy. Resulting ...
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