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GitHub9d

A self-supervised clustering method combining adversarial autoencoders with cross-attention-based graph convolutional networks (GCN) for cell type identification in scRNA-seq ...

The code runs under Python 3.9.20 and Pytorch 2.3.1+cu121. Create a PyTorch environment and install required packages, such as "numpy", "pandas", "scikit-learn ...
IEEE24d

Collaborative Evolutionary Multitasking Multiobjective Adversarial Attacks in Hyperspectral Image Classification

Abstract: Adversarial attacks on hyperspectral image (HSI) classification has garnered significant attention. However, most of the existing adversarial attack methods tend to apply global ...
IEEE26d

Evolutionary Adversarial Autoencoder for Unsupervised Anomaly Detection of Industrial Internet of Things

Abstract: The rapid growth of interconnected smart devices and advanced computing technologies in the industrial Internet of Things (IIoT) has significantly enhanced operational resilience and ...
GitHub26d

Discrepancy between PyTorch and TensorRT when casting from FP32 to BF16 causes significant accuracy mismatch

I encountered a reproducibility issue when exporting a PyTorch model to ONNX and running it with TensorRT in bfloat16 mode. Although the computation logic and operator mapping between PyTorch and ...