This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...

The transformer architecture has emerged as the ... 2 comments on “ KCL Leverages Topos Theory to Decode Transformer Architectures ” Pingback: KCL Leverages Topos Concept to Decode Transformer ...

Abstract: To develop an accurate segmentation model for the prostate and lesion area to help clinicians diagnose diseases, we propose a multi-encoder and decoder segmentation network, denoted ...

To address these difficulties, we propose an enhanced Seq2Seq model named TLGA, where the hierarchical Transformer-BiLSTM encoder can capture long-range interactions and sequential semantics while the ...

But not all transformer applications require both the encoder and decoder module. For example, the GPT family of large language models uses stacks of decoder modules to generate text.

Can the SwinTransformer with a Bart decoder be initialized using VisionEncoderDecoderModel or do I need to write my own model with SwinTransformer as enocder and Bart as decoder ? Metadata Assignees ...