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Thanks to Patrick and Bas for chatting about this over coffee after my lab meeting. Sounds like Lee had a very promising answer: Gaussian Processes!
Here are some potentially useful links I found by …
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similar error for any dataset I try:
```
python mesh_extract.py -s data/bicycle/ -m outputs/bicycle -r 2
Loaded gaussians from outputs/bicycle/point_cloud/iteration_7000/point_cloud.ply
Reading ca…
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Recently, there are many improved methods based on vanilla 3D Gaussian splatting. I have found that Scaffold-GS can significantly improve the reconstruction quality. Many scenarios where 3D Gaussian s…
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# 🚀 Feature Request
## Motivation
Student T Processes are the other member of the family of elliptical processes along with Gaussian Processes. In some situations these have preferable statist…
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Dear all,
I am using the package "brms" and I noticed that the package also supports Gaussian Processes with the function "gp", which I use a lot to model interactions between continuous predictors…
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```python
from sklearn.gaussian_process import GaussianProcess
```
Which show the Error message: `ImportError: cannot import name 'GaussianProcess'`
It may be raised by this function has been remo…
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Most of methods in the list will be implemented in the order.
- inference for Sparse Gaussian process regression (based on JMLR 2005 "A unifying view of sparse approximate Gaussian process regression…
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While Gaussian models are flexible and tractable, real data often exhibits noise with heavier tails than Gaussian. A popular model for robust estimation is Student's t distribution, e.g. as used in Sl…
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Is there anyone here who can help me run SIBR?
(hierarchical_3d_gaussians) kukla@DESKTOP-6AMN05S:/ hierarchical-3d-gaussians$ SIBR_viewers/install/bin/SIBR_gaussianHierarchyViewer_app --path ${DA…
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Well, I haven't saw the code for "Graph Convolutional Gaussian Processes for Link Prediction". LOL
I just wanna see some details about it.