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HICAI-ZJU
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KANO
Code and data for the Nature Machine Intelligence paper "Knowledge graph-enhanced molecular contrastive learning with functional prompt".
MIT License
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Question Regarding the Baseline Performance of CMPNN in Your Paper
#26
mxqmxqmxq
closed
2 weeks ago
5
Accessing other pre-trained models in Table 1 and 2
#25
yliu1240
opened
4 weeks ago
1
Where does augmentation happen in pretraining?
#24
soulios
opened
1 month ago
1
Questions about Fig.4.
#23
Vencent-Won
opened
6 months ago
0
关于图4中各官能团的注意力权重的大小（深浅）如何获得
#22
ABlueCat123
opened
6 months ago
2
关于官能团表是否有个小错误
#21
ABlueCat123
closed
8 months ago
2
Getting embeddings from the pretrained model
#20
rbvh
closed
9 months ago
3
关于将模型应用在下游预测任务的问题
#19
ABlueCat123
closed
10 months ago
6
关于如何绘制图3b
#18
wuyuhui-zju
closed
1 year ago
3
关于如何找文章中官能团知识图谱的数据
#17
cyli029
closed
1 year ago
2
functional_group 疑惑
#16
Sakura4036
closed
1 year ago
2
OWL File Understanding
#15
Pixelatory
closed
1 year ago
5
KGembeddings
#14
ZixuanFeng-NYU
closed
1 year ago
0
how to load the trained model and use it to predict on a second test set?
#13
WeiJunZhou23
closed
1 year ago
0
Dose `seed` affect the training when we set customized train/val/test set?
#12
WeiJunZhou23
closed
1 year ago
2
你好，我看预训练的时候，并没有使用Projection NetWork
#11
YunQingYangZzu
closed
1 year ago
1
calculation of train loss
#10
ZixuanFeng-NYU
closed
1 year ago
1
augmentation in pre-training
#9
ZixuanFeng-NYU
closed
1 year ago
1
How to get the prediction output seperately?
#8
WeiJunZhou23
closed
1 year ago
1
如何提取预训练特征来给其他下游模型进行训练？
#7
iPFAS
closed
1 year ago
2
pretrained_graph_encoder not include Prompt_generator weight
#6
danielkaifeng
closed
1 year ago
2
Problem of finetuning and predicting in custom dataset
#5
zw-SIMM
closed
1 year ago
2
Request for Specific Implementation in KANO
#4
Andy6M
closed
1 year ago
1
Prompt Implementation - Details Question
#3
vthost
closed
1 year ago
1
I'm having some problems with the pretrain program
#2
YunQingYangZzu
closed
1 year ago
2
About some performance comparison
#1
ghost
closed
1 year ago
3