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Maximilian Dax
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2020 – today
- 2024
- [i11]Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf:
Real-time gravitational-wave inference for binary neutron stars using machine learning. CoRR abs/2407.09602 (2024) - [i10]Vladimir Starostin, Maximilian Dax, Alexander Gerlach, Alexander Hinderhofer, Álvaro Tejero-Cantero
, Frank Schreiber:
Fast and Reliable Probabilistic Reflectometry Inversion with Prior-Amortized Neural Posterior Estimation. CoRR abs/2407.18648 (2024) - [i9]Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Annalena Kofler, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf:
Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels. CoRR abs/2410.21477 (2024) - 2023
- [c4]Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf:
Flow Matching for Scalable Simulation-Based Inference. NeurIPS 2023 - [i8]Maximilian Dax, Jonas Wildberger, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf:
Flow Matching for Scalable Simulation-Based Inference. CoRR abs/2305.17161 (2023) - [i7]Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf:
Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling. CoRR abs/2312.08295 (2023) - 2022
- [c3]Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke:
Group equivariant neural posterior estimation. ICLR 2022 - [i6]Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer
, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf:
Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference. CoRR abs/2210.05686 (2022) - [i5]Jonas Wildberger, Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer
, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf:
Adapting to noise distribution shifts in flow-based gravitational-wave inference. CoRR abs/2211.08801 (2022) - 2021
- [c2]Andong Tan, Duc Tam Nguyen, Maximilian Dax, Matthias Nießner, Thomas Brox:
Explicitly Modeled Attention Maps for Image Classification. AAAI 2021: 9799-9807 - [i4]Maximilian Dax, Stephen R. Green, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf:
Real-time gravitational-wave science with neural posterior estimation. CoRR abs/2106.12594 (2021) - [i3]Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke:
Group equivariant neural posterior estimation. CoRR abs/2111.13139 (2021) - 2020
- [i2]Andong Tan, Duc Tam Nguyen, Maximilian Dax, Matthias Nießner, Thomas Brox:
Explicitly Modeled Attention Maps for Image Classification. CoRR abs/2006.07872 (2020)
2010 – 2019
- 2019
- [c1]Duc Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi, Thi-Phuong-Nhung Ngo, Thi Hoai Phuong Nguyen, Zhongyu Lou, Thomas Brox:
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision. NeurIPS 2019: 204-214 - [i1]Duc Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi, Thi-Phuong-Nhung Ngo, Thi Hoai Phuong Nguyen, Zhongyu Lou, Thomas Brox:
DeepUSPS: Deep Robust Unsupervised Saliency Prediction With Self-Supervision. CoRR abs/1909.13055 (2019)
Coauthor Index

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last updated on 2024-12-01 00:17 CET by the dblp team
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