We only provide compatibility with nightly PyTorch, but you can check if stable PyTorch happens to be supported by looking at the following badge: TorchANI is a pytorch implementation of ANI. It is ...

This library provides the capability to emulate MX-compatble formats and bfloat quantization in pytorch, enabling data science exploration ... torch.bmm) between two MX tensors Elementwise ops (GELU, ...

With the incorporation of feature concatenation and an attention mechanism into the original YOLOv5s network, the improved YOLOv5s recorded 122 layers, 4.4 × 10 6 params, 12.8 GFLOPs, and 8.8 MB ...

The ability to work with tensors is fundamental in order to build models that can analyze and make decisions on large datasets. Two of the most popular tools for this purpose are PyTorch which was ...

As such, based on the self-supervised learning, this article proposes a spatial–spectral hierarchical multiscale transformer-based masked autoencoder (SSHMT-MAE) for HSI classification. First, after ...

In this paper, we introduce Time-DisCo, a Disentangled Contrastive autoencoder approach that integrates Transformers and autoencoders into a unified framework. In this framework, autoencoders ...