Max Horn

According to our database, Max Horn authored at least 24 papers between 2008 and 2023.

Collaborative distances:

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

2023

Representation Learning for Dimensionality Reduction, Irregularly-Sampled Sequences and Graphs.

Max Horn

PhD thesis, 2023

Unsupervised Open-Vocabulary Object Localization in Videos.

Ke Fan, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel, Mike Zheng Shou, Francesco Locatello, Bernt Schiele, Thomas Brox, Zheng Zhang, Yanwei Fu, Tong He

CoRR, 2023

A data augmentation perspective on diffusion models and retrieval.

Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell

CoRR, 2023

Bridging the Gap to Real-World Object-Centric Learning.

Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Object-Centric Multiple Object Tracking.

Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Unsupervised Open-Vocabulary Object Localization in Videos.

Ke Fan, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel, Mike Zheng Shou, Francesco Locatello, Bernt Schiele, Thomas Brox, Zheng Zhang, Yanwei Fu, Tong He

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning.

Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Assaying Out-Of-Distribution Generalization in Transfer Learning.

Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions.

Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the Tenth International Conference on Learning Representations, 2022

Topological Graph Neural Networks.

Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Pathologies in priors and inference for Bayesian transformers.

Tristan Cinquin, Alexander Immer, Max Horn, Vincent Fortuin

CoRR, 2021

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning.

Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt

CoRR, 2021

Translational Equivariance in Kernelizable Attention.

Max Horn, Kumar Shridhar, Elrich Groenewald, Philipp F. M. Baumann

CoRR, 2021

2020

Path Imputation Strategies for Signature Models.

Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck

CoRR, 2020

Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra.

Caroline Weis, Max Horn, Bastian Rieck, Aline Cuénod, Adrian Egli, Karsten M. Borgwardt

Bioinform., 2020

Topological Autoencoders.

Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the 37th International Conference on Machine Learning, 2020

Set Functions for Time Series.

Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Machine learning for early prediction of circulatory failure in the intensive care unit.

Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz

CoRR, 2019

Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis.

Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt

CoRR, 2019

Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping.

Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt

Proceedings of the Machine Learning for Healthcare Conference, 2019

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology.

Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt

Proceedings of the 7th International Conference on Learning Representations, 2019

2017

TRAPP webserver: predicting protein binding site flexibility and detecting transient binding pockets.

Antonia Stank, Daria B. Kokh, Max Horn, Elena Sizikova, Rebecca Neil, Joanna Panecka, Stefan Richter, Rebecca C. Wade

Nucleic Acids Res., 2017

2010

Computing Polycyclic Quotients of Finitely (L-)Presented Groups via Groebner Bases.

Bettina Eick, Max Horn

Proceedings of the Mathematical Software, 2010

2008

On the Phan system of the Schur cover of SU(4, 3²).

Max Horn

Des. Codes Cryptogr., 2008