Stochastic-Processes
Point-Processes
| Stochastic-Processes | Point-Processes | |
|---|---|---|
| 1 | 2 | |
| 30 | 37 | |
| - | - | |
| 6.4 | 0.0 | |
| about 1 year ago | over 1 year ago | |
| Python | Python | |
| - | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stochastic-Processes
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New Book: Gentle Introduction To Chaotic Dynamical Systems
Authored by Dr. Vincent Granville, 82 pages, published in March 2023. Available on our e-Store exclusively, here. See the table contents or sample chapter on GitHub here. The Python code is also in the same repository.
Point-Processes
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[R] DeepDPM: Deep Clustering With an Unknown Number of Clusters
https://github.com/VincentGranville/Point-Processes/commit/2c2ed7cc989711d0a40d96fb6f194c690fcded8f (left is original data)
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What is the hardest thing to learn in statistics?
As for confidence regions, you show them the a plot like this one. Each contour line defines a confidence region of a certain level (that can be determined accurately). This stuff is familiar to hikers using a map to navigate the terrain. No math involved in the whole teaching experience, other than stuff from elementary school.
What are some alternatives?
diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
dpmmpythonStreaming - Python wrapper for the DPMMSubClusterStreaming.jl Julia package.
pysindy - A package for the sparse identification of nonlinear dynamical systems from data
GPflow - Gaussian processes in TensorFlow
DeepDPM - "DeepDPM: Deep Clustering With An Unknown Number of Clusters" [Ronen, Finder, and Freifeld, CVPR 2022]
NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
dynamo-release - Inclusive model of expression dynamics with conventional or metabolic labeling based scRNA-seq / multiomics, vector field reconstruction and differential geometry analyses
torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.