The extraordinary ability of generative models to generate photographic
...
Recent releases of Large Language Models (LLMs), e.g. ChatGPT, are
aston...
At the heart of foundation models is the philosophy of "more is differen...
Recently, Multilayer Perceptron (MLP) becomes the hotspot in the field o...
We study the problem of learning from positive and unlabeled (PU) data i...
Adder neural network (AdderNet) is a new kind of deep model that replace...
Convolutional neural networks (CNN) have been widely used for boosting t...
Transformer is a type of deep neural network mainly based on self-attent...
As the computing power of modern hardware is increasing strongly, pre-tr...
This paper studies the single image super-resolution problem using adder...
Neural architecture search (NAS) aims to automatically design deep neura...
Despite Generative Adversarial Networks (GANs) have been widely used in
...
Quantization neural networks (QNNs) are very attractive to the industry
...
Compared with cheap addition operation, multiplication operation is of m...
Neural Architecture Search (NAS) is attractive for automatically produci...
Many attempts have been done to extend the great success of convolutiona...
Generative adversarial networks (GANs) have been successfully used for
c...
Learning portable neural networks is very essential for computer vision ...
Deep convolutional neural networks have been widely used in numerous
app...