ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...

According to @data_and_ai, out-of-the-box PyTorch models continue training even when the underlying infrastructure experiences failures, raising concerns about model reliability and consistency in ...

AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...

This is my comment when exporting: python3 onnx_export.py vit-s_baseline.onnx --model vit_small_patch16_224.augreg_in21k_ft_in1k --num-classes 1000 --img-size 224 This is my comment for evaluate .pth ...

Abstract: With the development of neural network technology, Spiking Neural Networks (SNNs) have shown great potential in edge computing and embedded systems due to their biologically inspired and low ...

I converted a PyTorch model to ONNX inside torch.autocast(device_type="cpu", dtype=torch.float16) context. When running inference on both the original and converted models, I observed that the ...