NEWPORT NEWS, Va. — The U.S. Army has taken a significant step to modernize how it manages Soldiers’ training data. On Nov. 15, ATIS Training — a streamlined, intuitive platform for managing ...
MASE-GC: a multi-omics autoencoder and stacking ensemble framework for gastric cancer classification
Background: Gastric cancer (GC) is one of the most common malignant tumors and remains a leading cause of cancer-related mortality worldwide. Accurate classification of GC is critical for improving ...
This AI Paper Introduces MAETok: A Masked Autoencoder-Based Tokenizer for Efficient Diffusion Models
Diffusion models generate images by progressively refining noise into structured representations. However, the computational cost associated with these models remains a key challenge, particularly ...
Which loss function did you use when training the autoencoder? Did you directly compute the MSE between the predicted SDF values and the ground truth? Additionally, how many steps did you train for?
Abstract: Large-scale pre-training models have promoted the development of histopathology image analysis. However, existing self-supervised methods for histopathology images primarily focus on ...
This manuscript presents the library AI4HPC with its architecture and components. The library enables large-scale trainings of AI models on High-Performance Computing systems. It addresses challenges ...
Abstract: In this paper, a signal-guided masked autoencoder (S-MAE) based semi-supervised learning framework is proposed for high-precision positioning with limited labeled channel impulse response ...
Preparing to run 26.2 miles can be daunting. Here’s how to structure four months of training. By Amanda Loudin When you cross the finish line of your first marathon, the high can make it easy to ...
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