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❗ This is a read-only mirror of the CRAN R package repository. pcalg — Methods for Graphical Models and Causal Inference. Homepage: https://pcalg.r-forge.r-project.org/
DYNAM-O: Dynamic Oscillation Toolbox v1.0 - Prerau Laboratory (sleepEEG.org)
A multitaper spectral estimation toolbox implemented in Matlab, Python, and R
State-space Oscillator Modeling And Time-series Analysis (SOMATA) is a Python library for state-space neural signal processing algorithms developed in the Purdon Lab.
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Create delightful software with Jupyter Notebooks
THOI: An efficient library for higher order interactions analysis based on Gaussian copulas enhanced by batch-processing
Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
Create powerful Hydra applications without the yaml files and boilerplate code.
Hidden Markov Models in Python, with scikit-learn like API
PyBADS: Bayesian Adaptive Direct Search optimization algorithm for model fitting in Python
Exploratory analysis of Bayesian models with Julia
Normalizing-flow enhanced sampling package for probabilistic inference in Jax
Kalman Filter, Smoother, and EM Algorithm for Python
State of the art inference for your bayesian models.
The code for paper: Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions [ICML 2024]
active learning + reusable workflows + likelihood free inference
PRML algorithms implemented in Python
A flexible toolkit for simulation based inference in Julia
Implements Optimization and approximate uncertainty quantification algorithms, Ensemble Kalman Inversion, and Ensemble Kalman Processes.
Free-form flows are a generative model training a pair of neural networks via maximum likelihood
Code to run dynamical simulations on a Kuramoto Network Model of Coupled Phase Oscillators with Time Delays and visualize the results.