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 ...
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 ...
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 ...
MathWorks, a leading developer of mathematical computing and simulation software, has revealed that a recent ransomware attack is behind an ongoing service outage. Headquartered in Natick, ...
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 ...
AutoencoderZ is an advanced Autoencoder model designed for dimensionality reduction of various data types, such as seismometer and strainmeter data. It features an encoder-decoder architecture that ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results