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 | 65 | 2020 |
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 | 48 | 2016 |
Quantum periods of Calabi–Yau fourfolds A Gerhardus, H Jockers Nuclear Physics B 913, 425-474, 2016 | 37 | 2016 |
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 | 23 | 2017 |
The geometry of gauged linear sigma model correlation functions A Gerhardus, H Jockers, U Ninad Nuclear Physics B 933, 65-133, 2018 | 15 | 2018 |
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 | 12 | 2023 |
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 | 8 | 2021 |
Discovering causal relations and equations from data G Camps-Valls, A Gerhardus, U Ninad, G Varando, G Martius, ... arXiv preprint arXiv:2305.13341, 2023 | 5 | 2023 |
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 | 3 | 2022 |
Characterization of causal ancestral graphs for time series with latent confounders A Gerhardus arXiv preprint arXiv:2112.08417, 2021 | 2 | 2021 |
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 | 1 | 2023 |
LPCMCI: Causal Discovery in Time Series with Latent Confounders A Gerhardus, J Runge | 1 | 2021 |
String Compactifications from the Worldsheet and Target Space Point of View A Gerhardus Universitäts-und Landesbibliothek Bonn, 2019 | 1 | 2019 |
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 |