selfattention

Injecting geometric priors into the Transformer modelContinue reading on Towards Data Science » Injecting geometric priors into the Transformer modelContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are the owner of the…

A deep dive into the application of the transformer architecture and its self-attention operation for visionImage created by author using craiyon AIWhile self-attention is already widely adopted in NLP and significantly contributes to the performance of state-of-the-art models (e.g. , ), more and more work is being done to achieve similar results in vision.Even though, there are hybrid approaches that combine for example CNNs with attention or apply linear transformations on patches of the image , a pure attention-based…

A practical overviewImage by author. AI-generated using Dall-E-2The Transformer architecture has been essential for some of the biggest breakthroughs in deep learning in recent years. Especially in the field of Natural Language Processing (NLP), pre-trained autoencoding models (like BERT ) and autoregressive models (like GPT-3 ) have continuously managed to outperform the state-of-the-art and reach human-like levels of text generation. One of the most important innovations of the Transformer is the use of attention…