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Maximilian Seitzer
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2020 – today
- 2024
- [c8]Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi:
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos. ICLR 2024 - [i10]Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael C. Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer:
Zero-Shot Object-Centric Representation Learning. CoRR abs/2408.09162 (2024) - 2023
- [c7]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 - [c6]Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius:
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities. NeurIPS 2023 - [i9]Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius:
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities. CoRR abs/2306.04829 (2023) - [i8]Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi:
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos. CoRR abs/2310.06020 (2023) - 2022
- [c5]Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic, Georg Martius:
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks. ICLR 2022 - [i7]Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic, Georg Martius:
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks. CoRR abs/2203.09168 (2022) - [i6]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
- [c4]Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius:
Self-supervised Visual Reinforcement Learning with Object-centric Representations. ICLR 2021 - [c3]Maximilian Seitzer, Bernhard Schölkopf, Georg Martius:
Causal Influence Detection for Improving Efficiency in Reinforcement Learning. NeurIPS 2021: 22905-22918 - [i5]Maximilian Seitzer, Bernhard Schölkopf, Georg Martius:
Causal Influence Detection for Improving Efficiency in Reinforcement Learning. CoRR abs/2106.03443 (2021) - 2020
- [i4]Maximilian Seitzer:
NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Aggregated Convolutional Feature Maps. CoRR abs/2002.10003 (2020) - [i3]Maximilian Seitzer, Andreas Foltyn, Felix P. Kemeth:
NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Learned Aggregation of Convolutional Feature Maps. CoRR abs/2002.12356 (2020) - [i2]Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius:
Self-supervised Visual Reinforcement Learning with Object-centric Representations. CoRR abs/2011.14381 (2020)
2010 – 2019
- 2018
- [c2]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:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. MICCAI (1) 2018: 232-240 - [i1]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:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. CoRR abs/1806.11216 (2018) - 2015
- [c1]Maximilian Seitzer, Michael Gruhn, Tilo Müller:
A Bytecode Interpreter for Secure Program Execution in Untrusted Main Memory. ESORICS (2) 2015: 376-395
Coauthor Index
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