GPflow
Point-Processes
| GPflow | Point-Processes | |
|---|---|---|
| 1 | 2 | |
| 1,799 | 37 | |
| 0.4% | - | |
| 5.8 | 0.0 | |
| 7 days ago | over 1 year ago | |
| Python | Python | |
| Apache License 2.0 | - |
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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.
GPflow
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?
whylogs - An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
dpmmpythonStreaming - Python wrapper for the DPMMSubClusterStreaming.jl Julia package.
mosec - A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
DeepDPM - "DeepDPM: Deep Clustering With An Unknown Number of Clusters" [Ronen, Finder, and Freifeld, CVPR 2022]
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
Stochastic-Processes - My book: Gentle Introduction to Chaotic Dynamical Systems. Includes stochastic dynamical systems and statistical properties of numeration systems in any dimension.
PILCO - Bayesian Reinforcement Learning in Tensorflow
uq-vae - Solving Bayesian Inverse Problems via Variational Autoencoders
vbmc - Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.