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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
872020
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
632023
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
522016
Quantum periods of Calabi–Yau fourfolds
A Gerhardus, H Jockers
Nuclear Physics B 913, 425-474, 2016
402016
Discovering causal relations and equations from data
G Camps-Valls, A Gerhardus, U Ninad, G Varando, G Martius, ...
Physics Reports 1044, 1-68, 2023
342023
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
262017
The geometry of gauged linear sigma model correlation functions
A Gerhardus, H Jockers, U Ninad
Nuclear Physics B 933, 65-133, 2018
152018
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
102021
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
72022
Characterization of causal ancestral graphs for time series with latent confounders
A Gerhardus
The Annals of Statistics 52 (1), 103-130, 2024
22024
Selecting robust features for machine-learning applications using multidata causal discovery
T Beucler, FIH Tam, MS Gomez, J Runge, A Gerhardus
Environmental Data Science 2, e27, 2023
22023
Bootstrap aggregation and confidence measures to improve time series causal discovery
K Debeire, A Gerhardus, J Runge, V Eyring
Causal Learning and Reasoning, 979-1007, 2024
12024
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
12023
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
12023
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
Causal Discovery in Ensembles of Climate Time Series
A Gerhardus, J Runge
EGU General Assembly Conference Abstracts, EGU22-6958, 2022
12022
String Compactifications from the Worldsheet and Target Space Point of View
A Gerhardus
Universitäts-und Landesbibliothek Bonn, 2019
12019
THE ANNALS
JC DUCHI, F RUAN, Z FAN, R LEDERMAN, YI SUN, T WANG, S XU, ...
The Annals of Statistics 52 (1), 2024
2024
Causal Feature Selection for Tropical Cyclone Intensity Forecasting
TG Beucler, SG SUDHEESH, FIH Tam, MS Gomez, M McGraw, ...
104th AMS Annual Meeting, 2024
2024
Novel developments in causal graphical models for time series
A Gerhardus
2023
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