indaba-pracs-2022
PyCBC-Tutorials
| indaba-pracs-2022 | PyCBC-Tutorials | |
|---|---|---|
| 1 | 2 | |
| 172 | 107 | |
| 0.6% | 0.9% | |
| 0.0 | 3.4 | |
| 29 days ago | 10 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
indaba-pracs-2022
-
From Deep Learning Foundations to Stable Diffusion
This year's Deep Learning Indaba had a tutorial on diffusion models in Jax: https://github.com/deep-learning-indaba/indaba-pracs-2022/tr...
PyCBC-Tutorials
- How can we use PSD for inverse spectrum truncation?
-
[GWpy] How do you know what time an event is occurring from a frequency plot?
If you want to get a sense for a signal is actually detected and at what time it occurs, I'd suggest taking a look at PyCBC and the tutorials there. https://github.com/gwastro/PyCBC-Tutorials In particular the following you may find useful, but you may find the others helpful as well. https://colab.research.google.com/github/gwastro/pycbc-tutorials/blob/master/tutorial/3\_WaveformMatchedFilter.ipynb
What are some alternatives?
neural-tangents - Fast and Easy Infinite Neural Networks in Python
pycbc - Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.
jaxrl - JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
pythoncode-tutorials - The Python Code Tutorials
pymc-resources - PyMC educational resources
bigpython - Source code for Big Python tutorials on YouTube
bodywork-pymc3-project - Serving Uncertainty with Bayesian inference, using PyMC3 with Bodywork
stingray - Anything can happen in the next half hour (including spectral timing made easy)!