Julius Kunze

According to our database, Julius Kunze authored at least 10 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Entropy Coding of Unordered Data Structures.

Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Phenaki: Variable Length Video Generation From Open Domain Textual Description.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan

CoRR, 2022

2021

Adaptive Optimization with Examplewise Gradients.

Julius Kunze, James Townsend, David Barber

CoRR, 2021

2020

HiLLoC: lossless image compression with hierarchical latent variable models.

James Townsend, Thomas Bird, Julius Kunze, David Barber

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Gaussian Mean Field Regularizes by Limiting Learned Information.

Julius Kunze, Louis Kirsch, Hippolyt Ritter, David Barber

Entropy, 2019

2018

Stochastic Variational Optimization.

Thomas Bird, Julius Kunze, David Barber

CoRR, 2018

Modular Networks: Learning to Decompose Neural Computation.

Louis Kirsch, Julius Kunze, David Barber

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Transfer Learning for Speech Recognition on a Budget.

Julius Kunze, Louis Kirsch, Ilia Kurenkov, Andreas Krug, Jens Johannsmeier, Sebastian Stober

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

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

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017