| SHI-Labs/Cross-Scale-Non-Local-Attention |
238 |
|
0 |
0 |
about 5 years ago |
0 |
|
9 |
|
Python |
| PyTorch code for our paper "Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining" (CVPR2020). |
| hjjpku/Attention_in_Graph |
27 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
|
Python |
| attention mechanism for graph classification, significant sub-graph mining, graph disstillation |
| AlexYangLi/ALA |
15 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
mit |
Python |
| Attention-based LSTM model with the Aspect information to solve financial opinion mining problem (WWW 2018 shared task1) |
| ppriyank/-Online-Soft-Mining-and-Class-Aware-Attention-Pytorch |
15 |
|
0 |
0 |
over 6 years ago |
0 |
|
2 |
|
Python |
| (Pytorch and Tensorflow) Implementation of Weighted Contrastive Loss (Deep Metric Learning by Online Soft Mining and Class-Aware Attention) |
| epochx/opinatt |
5 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
|
Python |
| Code and dataset for the paper "Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN" |
