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Hi, I have successfully ran through your code, but I have a question I want to communicate with you.
As shown in codes below, why you choose to compare the gap between predictedinput [i+1] and targ…
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Thanks for your great work!
I notice you use **layernorm** for the final features before the classifier and also for the predictions. I think it is quite uncommon in prototype learning (correct me if…
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### Search before asking
- [X] I have searched the YOLOv8 [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and fou…
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From: **Google Scholar Alerts**
Date: Sun, Mar 10,…
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Hi!I trained the model on the ultrasonic grayscale image, since there are only two classes, I changed the code to net = UNet(n_channels=1, n_classes=1, bilinear=True), and when I trained, the loss (ba…
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[Ratsgo's blog](https://ratsgo.github.io/machine%20learning/2017/11/10/CRF/)
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# Rational:
Machine learning models usually apply meta-parameter optimization to find the learning parameters that lead to the better learning and better cross-validation. So to here, to get a bio…
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I'm curious to know why by default the DeepAR model uses log loss (w/ activation regularization) according to these two links: [here](https://github.com/awslabs/gluon-ts/blob/master/src/gluonts/model/…
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Couple of strategy/scenarios
1) train-to-train model
- train a sub-class of PDEs with NeuralOperator
- transfer learning pre-trained prediction from NeuralOperator problem to PINNs
- PINNs train…