Abstract: This article presents a deep autoencoder-based methodology for unsupervised anomaly detection in centrifugal pumps under limited failure data conditions, focusing on real-world applications ...
Latent diffusion models have established a new state-of-the-art in high-resolution visual generation. Integrating Vision Foundation Model priors improves generative efficiency, yet existing latent ...
Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of conventional ...
Abstract: Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain ...
MATLAB is a leading environment for numerical computing, algorithm design, and data analysis used by engineers, researchers, and students worldwide. Prices matter because the total outlay depends on ...
Predicts velocity and pressure fields for various Reynolds numbers. Integrates CAE for dimensionality reduction and reconstruction. Uses LSTM to capture temporal dynamics for short-term predictions.
Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
Sparse autoencoders are central tools in analyzing how large language models function internally. Translating complex internal states into interpretable components allows researchers to break down ...
Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka 431-3192, Japan Department of Cellular and Molecular Anatomy, Hamamatsu University School of ...
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