Framework for Exploring and Understanding Multivariate Correlations. - Louis Kirsch; Niklas Riekenbrauck; Daniel Thevessen; Marcus Pappik; Axel Stebner; Julius Kunze; Alexander Meissner; Arvind Kumar Shekar; Emmanuel Müller (ECML/PKDD (3), 2017)

Transfer Learning for Speech Recognition on a Budget. - Julius Kunze; Louis Kirsch; Ilia Kurenkov; Andreas Krug; Jens Johannsmeier; Sebastian Stober (Rep4NLP@ACL, 2017)

Modular Networks: Learning to Decompose Neural Computation. - Louis Kirsch; Julius Kunze; David Barber (NeurIPS, 2018)

Stochastic Variational Optimization. - Thomas Bird; Julius Kunze; David Barber (CoRR, 2018)

Gaussian Mean Field Regularizes by Limiting Learned Information. - Julius Kunze; Louis Kirsch; Hippolyt Ritter; David Barber (Entropy, 2019)

HiLLoC: lossless image compression with hierarchical latent variable models. - James Townsend; Thomas Bird; Julius Kunze; David Barber (ICLR, 2020)

Adaptive Optimization with Examplewise Gradients. - Julius Kunze; James Townsend; David Barber (CoRR, 2021)

Phenaki: Variable Length Video Generation From Open Domain Textual Description. - Ruben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang 010; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan (CoRR, 2022)

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions. - Ruben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang 010; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan (ICLR, 2023)

Entropy Coding of Unordered Data Structures. - Julius Kunze; Daniel Severo 001; Giulio Zani; Jan-Willem van de Meent; James Townsend (ICLR, 2024)

Practical Shuffle Coding. - Julius Kunze; Daniel Severo 001; Jan-Willem van de Meent; James Townsend (NeurIPS, 2024)