There are 4 repositories under probabilistic-machine-learning topic.
[ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching
Code repository for the paper: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild (ICCV 2021)
Materials of the Nordic Probabilistic AI School 2019.
Explainable Machine Learning in Survival Analysis
Materials of the Nordic Probabilistic AI School 2021.
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Active Bayesian Causal Inference (Neurips'22)
Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.
Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023
The official repository for AAAI 2024 Oral paper "Structured Probabilistic Coding"
Awesome-spatial-temporal-scientific-machine-learning-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included.
A Bayesian Convolutional Neural Network model for classifying Cataract in Ocular Disease with measurements of uncertainty
Clean Random Events for Probabilistic Reasoning in Python
Repository of my notes and exercises on the course of Probabilistic Machine Learning by Prof. Luca Bortolussi at the University of Trieste in the year 2020/2021
🥚 EnerGy Guided Diffusion for optimizing neurally exciting images
headquarters of the April team in Edinburgh
Material for Philipp Hennig's course: Probabilistic Machine Learning, at Tubingen
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting (KDD 2023)
Tutorials on math epidemiology and epidemiology informed deep learning methods
Probabilistic modeling using PyStan with demonstrative case study experiments from Christopher Bishop's Model-based Machine Learning.
Coordinate Ascent Variational Inference for Dirichlet Process Mixtures of Gaussians
[AAAI 2019] "A Probabilistic Derivation of LASSO and L12-Norm Feature Selections", Di Ming, Chris Ding, Feiping Nie
Code for the research paper Meta-learning with hierarchical models based on similarity of causal mechanisms
List of casual implementations of machine learning models from scratch.
Probabilistic Learning and Reasoning Assignments
Repository for the Probabilistic Machine Learning labs/practica (@ UniTS, Spring 2023)
Predicting air pollution amounts in cities using a Gaussian Process model