Abstract: As modern System-on-chip (SoC) designs grow in complexity, traditional debug mechanisms involving manual waveform and log analysis struggle to keep up with the volume and intricacies of ...
New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as well as for bug fixing and identification. Now, one of its new studies ...
Apple has published three interesting studies that offer some insight into how AI-based development could improve workflows, quality, and productivity. Here are the details. Software Defect Prediction ...
A deep count autoencoder network to denoise scRNA-seq data and remove the dropout effect by taking the count structure, overdispersed nature and sparsity of the data into account using a deep ...
Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...
Abstract: Operations of power distribution systems with Distributed Energy Resources (DERs) can be managed in scalable manner with advanced distributed control algorithms. Distributed algorithms ...
Spatially resolved transcriptomics (SRT) technologies, such as spatial transcriptomics (ST) (Ståhl et al., 2016), 10x Visium, and Slide-seqV2 (Stickels et al., 2021), can measure the transcript ...
Molecular dynamics (MD) simulations have been actively used in the study of protein structure and function. However, extensive sampling in the protein conformational space requires large computational ...
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