The basic distribution probability Tutorial for Deep Learning Researchers
-
Updated
Oct 1, 2020 - Python
The basic distribution probability Tutorial for Deep Learning Researchers
Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows
Generate realizations of stochastic processes in python.
Normalizing flows in PyTorch
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
📃Language Model based sentences scoring library
📦 Python library for Stochastic Processes Simulation and Visualisation
Machine Learning with Symbolic Tensors
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
Likelihood-free AMortized Posterior Estimation with PyTorch
Markov Chains and Hidden Markov Models in Python
Probabilistic data structures in python http://pyprobables.readthedocs.io/en/latest/index.html
Probabilistic Programming and Statistical Inference in PyTorch
Autonomous Mobile Robot developed and programmed in the online course named "Self-Driving and ROS 2 - Learn By Doing! Odometry & Control"
A library for discrete-time Markov chains analysis.
Bayesian A/B testing
Completion After Prompt Probability. Make your LLM make a choice
Tools for an Aesara-based PPL.
Python dice probability package.
Add a description, image, and links to the probability topic page so that developers can more easily learn about it.
To associate your repository with the probability topic, visit your repo's landing page and select "manage topics."