Abstract: This paper proposes an application-oriented condition monitoring method for power semiconductor switches, which constructs a robust health indicator with high robustness, low sampling rate, ...
Bayesian regression with linear basis function models. Introduction to Bayesian linear regression. Implementation with plain NumPy and scikit-learn. See also PyMC3 implementation. Gaussian processes.
Latent Diffusion Autoencoders (LDAE) is a novel unsupervised framework for representation learning in 3D medical imaging. The method compresses 3D MRI scans using an AutoencoderKL, then applies a ...
Abstract: In this manuscript, we propose to use a variational autoencoder-based framework for parameterizing a conditional linear minimum mean squared error estimator ...
The sequence of amino acids within a protein dictates its structure and function. Protein engineering campaigns seek to discover protein sequences with desired functions. Data-driven models of the ...
Same as traditional autoencoders, VAE architecture has two parts: an encoder and a decoder. Traditional AE models map inputs into a latent-space vector and reconstruct the output from this vector. VAE ...
Image enhancement is considered to be one of the complex tasks in image processing. When the images are captured under dim light, the quality of the images degrades due to low visibility degenerating ...
Most existing image dehazing methods based learning are less able to perform well to real hazy images. An important reason is that they are trained on synthetic hazy images whose distribution is ...
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