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Hi everyone, before I delve deeper into my problem, I want to clarify that I'm using a simple RBF Kernel and a Gaussian likelihood function for the gpytorch model. We also have an embedding network th…
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## 🚀 Feature
It would be great if MixtureSameFamily had the rsample() functionality so as to make the parameters of the MixturesameFamily distribution trainable.
## Motivation
rsample() is a…
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Implement some of these models (probably in this order)
- [x] AE
- [ ] AE ensemble (or maybe KitNet?)
- [x] DAGMM = Deep autoencoding gaussian mixture model for unsupervised anomaly detection. Su…
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hi @dm13450 first of all thanks for the great JSS article / vignette about dirichletprocess, which is super helpful. I am using it for teaching a CS class about unsupervised learning algorithms this s…
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Soft Constrained Autonomous Vehicle Navigation using Gaussian Processes and Instance Segmentation. (arXiv:2101.06901v1 [cs.RO])
https://ift.tt/3ioyOsy
This paper presents a generic feature-based navig…
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The repository contains a `bayes_snapper.npy` that apparently contains a bayesian model to rate satellite quality. Unfortunately the model seems to have been generated with an outdated scikit version …
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hello,i would to know when a new speaker (not in data) ,how can deal with this state ,i read about this in paper (Speaker Verification Using Adapted Gaussian Mixture Models) to get final UBM combie I…
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Objective: Uncover the generative model behind these data samples
1. Assumption 1: The latent states can be uncovered from the principal modes of app usage behavior.
Test:
- [x] PCA dimensional…
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## Enhancement idea
- [x] Add Feature: Rational Quadratic Kernel (Support And Resistance Areas) Algorithm.
- [x] Connect to Alerts Modules and add custom alerts, see here: https://github.com/chart…