Using graph neural networks (GNNs) to approximate specific functions suc...
Table structure recognition aims to extract the logical and physical
str...
The Transformer-based encoder-decoder architecture has recently made
sig...
Persistent homology is a widely used theory in topological data analysis...
Inductive relation prediction is an important learning task for knowledg...
Encoder-decoder models have made great progress on handwritten mathemati...
Large-scale pre-trained models like BERT, have obtained a great success ...
Math expressions are important parts of scientific and educational docum...
Although the content in scientific publications is increasingly challeng...
Link prediction is an important learning task for graph-structured data....
Despite the recent advances in optical character recognition (OCR),
math...
Mathematical equations are an important part of dissemination and
commun...
Although the scientific digital library is growing at a rapid pace,
scho...
While the volume of scholarly publications has increased at a frenetic p...
One of the time-consuming routine work for a radiologist is to discern
a...
Skin cancer, the most common human malignancy, is primarily diagnosed
vi...