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ORCIDÁlvaro Tejero-Cantero
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2020 – today
- 2024
[j5]Timo Freiesleben
, Gunnar König, Christoph Molnar, Álvaro Tejero-Cantero:
Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena. Minds Mach. 34(3): 32 (2024)- [c2]Hanqi Zhou, Robert Bamler, Charley M. Wu, Álvaro Tejero-Cantero:
Predictive, scalable and interpretable knowledge tracing on structured domains. ICLR 2024 - [i7]Hanqi Zhou, Robert Bamler, Charley M. Wu, Álvaro Tejero-Cantero:
Predictive, scalable and interpretable knowledge tracing on structured domains. CoRR abs/2403.13179 (2024) - [i6]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) - [i5]Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke:
sbi reloaded: a toolkit for simulation-based inference workflows. CoRR abs/2411.17337 (2024) - 2022
- [c1]Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts, Álvaro Tejero-Cantero, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke:
GATSBI: Generative Adversarial Training for Simulation-Based Inference. ICLR 2022 - [i4]Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts, Álvaro Tejero-Cantero, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke:
GATSBI: Generative Adversarial Training for Simulation-Based Inference. CoRR abs/2203.06481 (2022) - [i3]Timo Freiesleben, Gunnar König, Christoph Molnar, Álvaro Tejero-Cantero:
Scientific Inference With Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena. CoRR abs/2206.05487 (2022) - [i2]Seth D. Axen, Alexandra Gessner, Christian Sommer, Nils Weitzel, Álvaro Tejero-Cantero:
Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes. CoRR abs/2211.08160 (2022) - 2020
- [j4]Álvaro Tejero-Cantero, Jan Boelts, Michael Deistler, Jan-Matthis Lueckmann, Conor Durkan, Pedro J. Gonçalves, David S. Greenberg, Jakob H. Macke:
sbi: A toolkit for simulation-based inference. J. Open Source Softw. 5(52): 2505 (2020) - [i1]Álvaro Tejero-Cantero, Jan Boelts, Michael Deistler, Jan-Matthis Lueckmann, Conor Durkan, Pedro J. Gonçalves, David S. Greenberg, Jakob H. Macke:
SBI - A toolkit for simulation-based inference. CoRR abs/2007.09114 (2020)
2010 – 2019
- 2016
- [j3]Diego Vidaurre, Andrew J. Quinn, Adam P. Baker, David Dupret, Álvaro Tejero-Cantero, Mark W. Woolrich:
Spectrally resolved fast transient brain states in electrophysiological data. NeuroImage 126: 81-95 (2016) - 2014
- [j2]Philipp L. Rautenberg, Ajayrama Kumaraswamy, Álvaro Tejero-Cantero, Christoph Doblander, Mohammad Norouzian, Kazuki Kai, Hans-Arno Jacobsen, Hiroyuki Ai, Thomas Wachtler, Hidetoshi Ikeno:
NeuronDepot: keeping your colleagues in sync by combining modern cloud storage services, the local file system, and simple web applications. Frontiers Neuroinformatics 8: 55 (2014) - 2013
- [j1]Axel Kammerer, Álvaro Tejero-Cantero, Christian Leibold:
Inhibition enhances memory capacity: optimal feedback, transient replay and oscillations. J. Comput. Neurosci. 34(1): 125-136 (2013)
Coauthor Index
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