Publications
Here is a list of all my publications (excluding conference abstracts). Alternatively, you can also take a lookt at my Google Scholar profile, or search for me on NASA/ADS.
Comparing Apples with Apples: Robust Detection Limits for Exoplanet High-Contrast Imaging in the Presence of non-Gaussian Noise
Markus J. Bonse, Emily O. Garvin, Timothy D. Gebhard, Felix A. Dannert, Faustine Cantalloube, Gabriele Cugno, Olivier Absil, Jean Hayoz, Julien Milli, Markus Kasper, Sascha P. Quanz
Under Review,
Inferring molecular complexity from mass spectrometry data using machine learning
Timothy D. Gebhard*, Aaron C. Bell*, Jian Gong*, Jaden J. A. Hastings*, G. Matthew Fricke, Nathalie Cabrol, Scott Sandford, Michael Phillips, Kimberley Warren-Rhodes, Atılım Güneş Baydin
Accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2022,
Atmospheric retrievals of exoplanets using learned parameterizations of pressure-temperature profiles
Timothy D. Gebhard, Daniel Angerhausen, Björn Konrad, Eleonora Alei, Sascha P. Quanz, Bernhard Schölkopf
Accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2022,
Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework
Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf
Astronomy & Astrophysics, 666 (A9),
Physically constrained causal noise models for high-contrast imaging of exoplanets
Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf
Accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2020,
Enhancing Gravitational-Wave Science with Machine Learning
Elena Cuoco, Jade Powell, Marco Cavaglià, Kendall Ackley, Michał Bejger, Chayan Chatterjee, Michael Coughlin, Scott Coughlin, Paul Easter, Reed Essick, Hunter Gabbard, Timothy Gebhard, Shaon Ghosh, Leïla Haegel, Alberto Iess, David Keitel, Zsuzsa Márka, Szabolcs Márka, Filip Morawski, Tri Nguyen, Rich Ormiston, Michael Puerrer, Massimiliano Razzano, Kai Staats, Gabriele Vajente, Daniel Williams
Machine Learning: Science and Technology, 2 (1),
Convolutional neural networks: A magic bullet for gravitational-wave detection?
Timothy D. Gebhard*, Niki Kilbertus*, Ian Harry, Bernhard Schölkopf
Physical Review D, 100 (6),
ConvWave: Searching for Gravitational Waves with Fully Convolutional Neural Nets
Timothy Gebhard*, Niki Kilbertus*, Giambattista Parascandolo, Ian Harry, Bernhard Schölkopf
Accepted at the Deep Learning for Physical Sciences workshop at NeurIPS 2017,
Software Quality Control at Belle II
Martin Ritter, Thomas Kuhr, Thomas Hauth, Timothy Gebhard, Michal Kristof, Christian Pulvermacher
Journal of Physics: Conference Series, Volume 898,
Sample Size Estimation for Outlier Detection
Timothy Gebhard, Inga Koerte, Sylvain Bouix
18th International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI 2015),