Maximilian Seitzer

According to our database, Maximilian Seitzer authored at least 11 papers between 2015 and 2024.

Collaborative distances:

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

2024

Zero-Shot Object-Centric Representation Learning.

Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael C. Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer

CoRR, 2024

DyST: Towards Dynamic Neural Scene Representations on Real-World Videos.

Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities.

Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

2022

On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks.

Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic, Georg Martius

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Causal Influence Detection for Improving Efficiency in Reinforcement Learning.

Maximilian Seitzer, Bernhard Schölkopf, Georg Martius

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self-supervised Visual Reinforcement Learning with Object-centric Representations.

Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Learned Aggregation of Convolutional Feature Maps.

Maximilian Seitzer, Andreas Foltyn, Felix P. Kemeth

CoRR, 2020

NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Aggregated Convolutional Feature Maps.

Maximilian Seitzer

CoRR, 2020

2018

Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction.

Maximilian Seitzer, Guang Yang, Jo Schlemper, Ozan Oktay, Tobias Würfl, Vincent Christlein, Tom Wong, Raad Mohiaddin, David N. Firmin, Jennifer Keegan, Daniel Rueckert, Andreas K. Maier

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2015

A Bytecode Interpreter for Secure Program Execution in Untrusted Main Memory.

Maximilian Seitzer, Michael Gruhn, Tilo Müller

Proceedings of the Computer Security - ESORICS 2015, 2015