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The exponential family consists of probability density functions that have the form $h(x) * \exp(\eta^T t(x) + a(\eta)).
Riksi updated
3 years ago
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Had a brief discussion with @williamjameshandley offline about using normalizing flows (NFs) as Neural Density Estimators (NDEs) instead of KDEs for production-grade anesthetic plots. I've been doing …
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Hi,
Really interesting work on categorical normalising flows (CNF), I'm reading your paper now.
I'm interesting in applying normalising flows to generic tabular datasets that can have both conti…
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您好，非常棒的工作，我仔细看了您的训练代码，并未发现训练pose标准化流的代码，请问会发布训练pose标准化流的代码吗？
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## 🚀 Feature
**Original Paper**
https://arxiv.org/abs/1905.13177
**Original Paper TensorFlow Repo**
https://github.com/jliu/graph-normalizing-flows
**Motivation**
A very interesting paper …
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The "number of parameter updates" in the paper is quite ambiguous and using the interpretation we currently have our models are not performing anywhere near as well. Any thoughts on it?
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I recently found about NESSAI and I'm trying to implement some of my analysis of radial velocity time-series (for exoplanets) to test the performance compared to dynesty, as I have a few problems whic…
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Will there be collection for cvpr 2023?
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> ValueError: Reverse-mode differentiation does not work for lax.while_loop or lax.fori_loop with dynamic start/stop values. Try using lax.scan, or using fori_loop with static start/stop.
I would l…
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Currently the [weight_norm](https://github.com/pytorch/pytorch/blob/master/torch/nn/utils/weight_norm.py) and [spectral_norm](https://github.com/pytorch/pytorch/blob/master/torch/nn/utils/spectral_nor…