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ORCIDMax Horn
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2020 – today
- 2024
[c13]Ke Fan, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, Zheng Zhang:
Adaptive Slot Attention: Object Discovery with Dynamic Slot Number. CVPR 2024: 23062-23071- [i18]Ke Fan, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, Zheng Zhang:
Adaptive Slot Attention: Object Discovery with Dynamic Slot Number. CoRR abs/2406.09196 (2024) - 2023
- [b1]Max Horn:
Representation Learning for Dimensionality Reduction, Irregularly-Sampled Sequences and Graphs. ETH Zurich, Zürich, Switzerland, 2023 - [j4]Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell:
Image retrieval outperforms diffusion models on data augmentation. Trans. Mach. Learn. Res. 2023 (2023) - [c12]Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello:
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CLeaR 2023: 553-573 - [c11]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:
Unsupervised Open-Vocabulary Object Localization in Videos. ICCV 2023: 13701-13709 - [c10]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:
Object-Centric Multiple Object Tracking. ICCV 2023: 16555-16565 - [c9]Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello:
Bridging the Gap to Real-World Object-Centric Learning. ICLR 2023 - [i17]Yuejiang Liu, Alexandre Alahi, Chris Russell
, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello:
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CoRR abs/2301.05169 (2023) - [i16]Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell:
A data augmentation perspective on diffusion models and retrieval. CoRR abs/2304.10253 (2023) - [i15]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:
Object-Centric Multiple Object Tracking. CoRR abs/2309.00233 (2023) - [i14]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:
Unsupervised Open-Vocabulary Object Localization in Videos. CoRR abs/2309.09858 (2023) - 2022
- [c8]Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt:
Topological Graph Neural Networks. ICLR 2022 - [c7]Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt:
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. ICLR 2022 - [c6]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:
Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS 2022 - [i13]Florian Wenzel, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello:
Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR abs/2207.09239 (2022) - [i12]Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello:
Bridging the Gap to Real-World Object-Centric Learning. CoRR abs/2209.14860 (2022) - 2021
- [i11]Max Horn, Kumar Shridhar, Elrich Groenewald, Philipp F. M. Baumann:
Translational Equivariance in Kernelizable Attention. CoRR abs/2102.07680 (2021) - [i10]Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt:
Topological Graph Neural Networks. CoRR abs/2102.07835 (2021) - [i9]Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt:
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. CoRR abs/2106.01098 (2021) - [i8]Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt:
Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. CoRR abs/2107.05230 (2021) - [i7]Tristan Cinquin, Alexander Immer, Max Horn, Vincent Fortuin:
Pathologies in priors and inference for Bayesian transformers. CoRR abs/2110.04020 (2021) - 2020
- [j3]Caroline Weis, Max Horn, Bastian Rieck, Aline Cuénod, Adrian Egli, Karsten M. Borgwardt:
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra. Bioinform. 36(Supplement-1): i30-i38 (2020) - [c5]Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt:
Set Functions for Time Series. ICML 2020: 4353-4363 - [c4]Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt:
Topological Autoencoders. ICML 2020: 7045-7054 - [i6]Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck:
Path Imputation Strategies for Signature Models. CoRR abs/2005.12359 (2020)
2010 – 2019
- 2019
- [c3]Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt:
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. ICLR (Poster) 2019 - [c2]Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt:
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. MLHC 2019: 2-26 - [i5]Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt:
Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. CoRR abs/1902.01659 (2019) - [i4]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:
Machine learning for early prediction of circulatory failure in the intensive care unit. CoRR abs/1904.07990 (2019) - [i3]Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt:
Topological Autoencoders. CoRR abs/1906.00722 (2019) - [i2]Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt:
Set Functions for Time Series. CoRR abs/1909.12064 (2019) - 2018
- [i1]Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt:
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. CoRR abs/1812.09764 (2018) - 2017
- [j2]Antonia Stank, Daria B. Kokh, Max Horn, Elena Sizikova, Rebecca Neil, Joanna Panecka, Stefan Richter, Rebecca C. Wade:
TRAPP webserver: predicting protein binding site flexibility and detecting transient binding pockets. Nucleic Acids Res. 45(Webserver-Issue): W325-W330 (2017) - 2010
- [c1]Bettina Eick, Max Horn:
Computing Polycyclic Quotients of Finitely (L-)Presented Groups via Groebner Bases. ICMS 2010: 50-53
2000 – 2009
- 2008
- [j1]Max Horn:
On the Phan system of the Schur cover of SU(4, 32). Des. Codes Cryptogr. 47(1-3): 243-247 (2008)
Coauthor Index
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