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### Repository commit
03a42510b01c574292ca9c6525cbf0572ff5a2a5
### Python version (python --version)
Python 3.10.15
### Dependencies version (pip freeze)
absl-py==2.1.0
astunparse==1.6.3
beauti…
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I think it could be usefull to find a notion of KL divergence between two metacommunities. Probably, these could come in Alpha, Gamma, or Beta flavors. The KL divergence $KL(p||q)$ is defined by
$K…
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# [GAN study] KL-divergence & JS-divergence & Maximum Likelihood Estimation와 개념정리 - zzennin’s DeepLearning
entropy와 cross entropy, MLE
[https://chaelin0722.github.io/gan/KL_divergence&JS_divergence/…
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AFAIK, the following features aren't available right now in `sympy.stats`,
1. Kullback–Leibler divergence - https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence
2. Reparametrizing one…
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Why is KL divergence not used in the loss?
a1wj1 updated
11 months ago
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When I look at your function at ae.py#L138, and compare it to https://stat.duke.edu/courses/Spring09/sta205/lec/hoef.pdf (in the middle of page 2) it seems like there should be different bracketing : …
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can you give some explanations of the KL divergence term? I am a little bit confused
kl_loss = torch.mean(0.5 * torch.sum(torch.exp(logvar) + mu**2 - 1 - logvar, 1))
Thank you so much!
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### 🚀 The feature, motivation and pitch
TVD is a good distance metric ([ref](https://aclanthology.org/2023.acl-long.605.pdf)) and easy to implement kernel to make the gradient more stable compared …
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Hello, in the provided `evaluator.py`:
```python
def compute_inception_score(self, activations: np.ndarray, split_size: int = 5000) -> float:
softmax_out = []
for i in range(…