Software platform for Thermodynamic Sampling Units - probabilistic computing emulator

A problemset for uncertainty quantification and knowledge injection into reinforcement learning and active inference agents

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

This is the official code for calibration in multi-hypothesis human pose estimation

Bayesian Optimization

Core Machine Learning concepts , algorithms & maths implemented completely from scratch using Python & numpy only.

We present a probabilistic model for neural spike counts that can capture arbitrary single neuron and joint statistics with their modulation by external covariates.

PyTorch implementation of a variational autoencoder (VAE) for use on multi-channel 2D data such as images

Probabilistic modeling of high-dimensional binary data in JAX

Exercises in the subject "Probabilistic Machine Learning" at Hasso Plattner Institute.

Final Project from the course "Probabilistic Machine Learning" @ Data Science & Scientific Computing, University of Trieste, year 2020/2021, written in ipynb.

Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting (KDD 2023)

Seminar in Probabilistic Machine Learning

Probabilistic modeling through Bayesian inference using PyStan with demonstrative case study experiments from Christopher Bishop's Model-based Machine Learning.

[AAAI 2019] "A Probabilistic Derivation of LASSO and L12-Norm Feature Selections", Di Ming, Chris Ding, Feiping Nie