Jakub Tomczak

intro_dgm. "Deep Generative Modeling": Introductory Examples

vae_vampprior. Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling

vae_vpflows. Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling

vae_householder_flow. Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)

git_flow. General Invertible Transformations for Flow-based Generative Models

crash-course-diffusion. A crash course in diffusion-based models

vae_kan_example. A simple example of VAEs with KANs

reversible-de. Differential Evolution with Reversible Linear Transformations

vibeprompter. VibePrompter is a desktop app for visually designing process flows with typed inputs/outputs, validating connections, and exporting diagrams as JSON or LLM-ready prompts. Built with Python and pywebview, it provides a native, lightweight interface for turning workflows into implementation-ready specifications.

sylvester-flows. Python

jmtomczak.github.io. My webpage

AttentionDeepMIL. Implementation of Attention-based Deep Multiple Instance Learning in PyTorch

PixelVAE. Code for the models in "PixelVAE: A Latent Variable Model for Natural Images" (https://arxiv.org/abs/1611.05013

popi4sb. Population-based Parameter Identification for Systems Biology

lightMM. lightMM: a novel tool for calculating kinetic constants in the Michaelis-Menten equation from two substrate concentrations