China Researchers Propose iTransformer: Rethink Transformer Architecture to Improve Time Series Forecasting
Transformer has become the basic model that adheres to the scaling rule after achieving great success in natural language processing ...
Tag: Transformer
Reimagining Image Recognition: Introducing Google’s Vision Transformer (ViT) Model Paradigm Shift in Visual Data Processing
In image recognition, researchers and developers are constantly seeking innovative approaches to improve the accuracy and efficiency of computer vision ...
Meet MatFormer: A Universal Nested Transformer Architecture for Flexible Model Deployment Across Platforms
Transformer models find applications in various applications, from powerful multi-throttle groups to individual mobile devices. The varied inference requirements in ...
UC Berkeley Researchers Propose RingAttention: A Memory-Efficient AI Approach to Reduce Transformer Memory Requirements
One type of deep learning model architecture is called Transformers in the context of many next-generation ai models. They have ...
Google DeepMind researchers discover scalable solutions to combat training instabilities in transformer models: an in-depth look at smaller-scale optimization and reproducibility strategies
An innovative advancement in the field of artificial intelligence is the expansion of Transformers. It has enabled major advances in ...
Meet ProPainter: An Improved AI Framework for Video Painting (VI) with Improved Propagation and an Efficient Transformer
The field of artificial intelligence is evolving like anything. One of its main subfields, the well-known computer vision, has gained ...
FastViT: A Fast Hybrid Vision Transformer Using Structural Reparametrization
The recent fusion of convolutional and transformer designs has led to constant improvements in model accuracy and efficiency. In this ...
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