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I'm new to TFP and probabilistic models. With deterministic NNs, I could balance my data by oversampling. However, my intuition says one shouldn't do this with probabilistic networks.
Currently, I'…
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### 🚀 The feature
For each classification datasets with balanced distribution on the classes (MNIST, CIFAR-N, etc...), it would be very useful to provide a standard dataset for the imbalanced versi…
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Dear Scimap Team,
Thank you for your exceptional work in advancing spatial-omics biology. I am currently facing a challenge with integrating two different scales of CODEX quantification data proc…
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Training of Mask R-CNN in the current implementation can suffer from class imbalance. As all selected training proposals are treated as the same class, objects that are more abundant than others will …
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I'm using Gtk3 backend but I have issue while running and using custom canvas controls, here is the execption:
```
Managed Debugging Assistant 'PInvokeStackImbalance' has detected a problem in 'D:\En…
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E. Triantafillou et. al. [1] had experiments for few-shot learning with class imbalance to see if the class imbalance actually impacts to the performance of the few-shot learning methods.
**Resul…
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This feature should take into consideration users Bioresonance-Test-Report markers like food items, non food items that a user is allergic to, nutritional imbalances, metal sensitivities, hormonal imb…
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I have tried to modify the caret function: learning_curve_dat, for taking into account class imbalances. learning_curve_dat uses a simple sample function to obtain the `in_mod` parameter. So, I have u…
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Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with…
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I wonder if the strategy I'm using in the tutorial is actually suitable for imbalanced designs. For example, let's say I had 3 replicates in one batch and 6 replicates in a another batch and am creati…