The Laplace Bridge for Bayesian Neural Networks

Easy-to-understand summary of our paper: Fast Predictive Uncertainty for Classification with Bayesian Deep Networks (Updated in 2022)

Posted by Marius Hobbhahn on May 29, 2022
Tags: Machine Learning Laplace Bridge

Laplace Matching for Generalized Linear Models

Easy-to-understand summary of my first Ph.D. paper

Posted by Marius Hobbhahn on November 10, 2021
Tags: Machine Learning

A (visual) Tutorial on Exponential Families

With focus on Machine Learning

Posted by Marius Hobbhahn on June 10, 2021
Tags: Machine Learning

Change of variable for PDFs

A simple visual tutorial

Posted by Marius Hobbhahn on May 20, 2021
Tags: Machine Learning

Sums and products of random variables vs. probability density functions

A tutorial in pictures

Posted by Marius Hobbhahn on April 29, 2021
Tags: Machine Learning

Sequence Classification using Ensembles of Recurrent Generative Expert Modules

Easy-to-understand summary of a paper that we published at ESANN2020

Posted by Marius Hobbhahn on September 12, 2020
Tags: Machine Learning Inverse Classification

Inverse Classification using GANs

A summary of exploratory work on the usage of GANs for Inverse Classification

Posted by Marius Hobbhahn on May 9, 2020
Tags: Machine Learning Inverse Classification

The reproducibility crisis in Machine Learning

Posted by Marius Hobbhahn on March 22, 2020
Tags: Machine Learning

A reproducibility ML journal

Posted by Marius Hobbhahn on March 22, 2020
Tags: Machine Learning

Using the Scattering Transform for Object Detection

This post is a summary of my second bachelor thesis (Computer Science)

Posted by Marius Hobbhahn on October 25, 2019
Tags: Machine Learning

Inverse Classification using Generative Models

This post is a summary of my first bachelor thesis (Cognitive Science)

Posted by Marius Hobbhahn on October 20, 2019
Tags: Machine Learning Inverse Classification