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Andreas Gerhardus
Andreas Gerhardus
Institute of Data Science, German Aerospace Center (DLR)
Bestätigte E-Mail-Adresse bei dlr.de
Titel
Zitiert von
Zitiert von
Jahr
High-recall causal discovery for autocorrelated time series with latent confounders
A Gerhardus, J Runge
Advances in Neural Information Processing Systems 33, 12615-12625, 2020
652020
Search for the effect of massive bodies on atomic spectra and constraints on Yukawa-type interactions of scalar particles
N Leefer, A Gerhardus, D Budker, VV Flambaum, YV Stadnik
Physical review letters 117 (27), 271601, 2016
482016
Quantum periods of Calabi–Yau fourfolds
A Gerhardus, H Jockers
Nuclear Physics B 913, 425-474, 2016
372016
Dual pairs of gauged linear sigma models and derived equivalences of Calabi–Yau threefolds
A Gerhardus, H Jockers
Journal of Geometry and Physics 114, 223-259, 2017
232017
The geometry of gauged linear sigma model correlation functions
A Gerhardus, H Jockers, U Ninad
Nuclear Physics B 933, 65-133, 2018
152018
Causal inference for time series
J Runge, A Gerhardus, G Varando, V Eyring, G Camps-Valls
Nature Reviews Earth & Environment 4 (7), 487-505, 2023
122023
Supersymmetric black holes and the SJT/nSCFT1 correspondence
S Förste, A Gerhardus, J Kames-King
Journal of High Energy Physics 2021 (1), 1-44, 2021
82021
Discovering causal relations and equations from data
G Camps-Valls, A Gerhardus, U Ninad, G Varando, G Martius, ...
arXiv preprint arXiv:2305.13341, 2023
52023
A spatiotemporal stochastic climate model for benchmarking causal discovery methods for teleconnections
XA Tibau, C Reimers, A Gerhardus, J Denzler, V Eyring, J Runge
Environmental Data Science 1, e12, 2022
32022
Characterization of causal ancestral graphs for time series with latent confounders
A Gerhardus
arXiv preprint arXiv:2112.08417, 2021
22021
Formalising causal inference in time and frequency on process graphs with latent components
ND Reiter, A Gerhardus, J Wahl, J Runge
arXiv preprint arXiv:2305.11561, 2023
12023
LPCMCI: Causal Discovery in Time Series with Latent Confounders
A Gerhardus, J Runge
12021
String Compactifications from the Worldsheet and Target Space Point of View
A Gerhardus
Universitäts-und Landesbibliothek Bonn, 2019
12019
Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation
OI Popescu, A Gerhardus, J Runge
arXiv preprint arXiv:2310.11132, 2023
2023
Projecting infinite time series graphs to finite marginal graphs using number theory
A Gerhardus, J Wahl, S Faltenbacher, U Ninad, J Runge
arXiv preprint arXiv:2310.05526, 2023
2023
Publisher Correction: Causal inference for time series
J Runge, A Gerhardus, G Varando, V Eyring, G Camps-Valls
Nature Reviews Earth & Environment 4 (8), 596-596, 2023
2023
Increasing effect sizes of pairwise conditional independence tests between random vectors
T Hochsprung, J Wahl, A Gerhardus, U Ninad, J Runge
Uncertainty in Artificial Intelligence, 879-889, 2023
2023
Bootstrap aggregation and confidence measures to improve time series causal discovery
K Debeire, J Runge, A Gerhardus, V Eyring
arXiv preprint arXiv:2306.08946, 2023
2023
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery
T Beucler, FIH Tam, MS Gomez, J Runge, A Gerhardus
arXiv preprint arXiv:2304.05294, 2023
2023
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery
S Saranya Ganesh, T Beucler, F Iat-Hin Tam, MS Gomez, J Runge, ...
arXiv e-prints, arXiv: 2304.05294, 2023
2023
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