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https://arxiv.org/pdf/2207.08200
this paper provides a different way to optimize the priors using distance aware priors.
Maybe i can try to implement it.
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I went deep through the rabbit hole of uncertainty quantification in forecasting of neural networks. A faster method of quantifying uncertainty than what was proposed by [Lapeyrolerie et al, 2022](htt…
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1.HoloPose: Holistic 3D Human Reconstruction In-The-Wild(2019)
mixture-of-experts rotation prior, part-based modeling( features co-varies with joint position)
code: can not open [http://arielai.com/…
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> [!NOTE]
> If you have a request to support a specific method, or would like to see priority of one of the listed methods, please open a separate issue, so it won't get buried in this thread. Base…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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Hi,
I am really interested in calculating the uncertainty using graph neural networks and I am going through your paper. I was wondering if you can provide some ipynb notebook to train such models a…
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# UQ4ML – Uncertainty Quantification Techniques in Machine Learning Models
This session focuses on uncertainty quantification (UQ) techniques in machine learning models and their applications acros…
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# Uncertainty Quantification of ML models: From Introduction to Advanced
# Responsible person(s)
Sebastian Starke, , HZDR,
Steve Schmerler, HZDR, @elcorto
Peter Steinbach, HZDR, @psteinb
G…
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Hi, I have read your explanation about Bayesian neural network, aleatoric uncertainty and epistemic uncertainty. It is very excellent and straightforward. But I also notice an interesting phenomenon t…
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Steps and tasks to be done for gender bias mitigation in OpeNTF:
**1. Related works**
- [x] Learning to form skill-based teams of experts.
- [x] Bootless Application of Greedy Re-ranking Algorit…