| 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 | 47 | 2016 |
| 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 | 43 | 2020 |
| Quantum periods of Calabi–Yau fourfolds A Gerhardus, H Jockers Nuclear Physics B 913, 425-474, 2016 | 35 | 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 |
| 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 | 7 | 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 | 1 | 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 | 1 | 2022 |
| Characterization of causal ancestral graphs for time series with latent confounders A Gerhardus arXiv preprint arXiv:2112.08417, 2021 | 1 | 2021 |
| String Compactifications from the Worldsheet and Target Space Point of View A Gerhardus Universitäts-und Landesbibliothek Bonn, 2019 | 1 | 2019 |
| 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 | | 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 |
| Causal Discovery to Improve Machine Learning-Based Tropical Cyclone Intensity Predictions SG Sudheesh, TG Beucler, FIH Tam, A Gerhardus, J Runge 103rd AMS Annual Meeting, 2023 | | 2023 |
| A spatiotemporal stochastic climate model for benchmarking causal discovery methods for teleconnections–CORRIGENDUM XA Tibau, C Reimers, A Gerhardus, J Denzler, V Eyring, J Runge Environmental Data Science 2, e4, 2023 | | 2023 |
| Understanding and predicting the interannual variability (IAV) of the global terrestrial carbon cycle J Wen, J Runge, A Gerhardus, Y SUN AGU Fall Meeting Abstracts 2022, B42H-1725, 2022 | | 2022 |
| Causal inference for temporal patterns ND Reiter, A Gerhardus, J Runge arXiv preprint arXiv:2205.15149, 2022 | | 2022 |
| Causal Discovery in Ensembles of Climate Time Series A Gerhardus, J Runge EGU General Assembly Conference Abstracts, EGU22-6958, 2022 | | 2022 |
| Causal Orthogonal Functions: A Causal Inference approach to temporal feature extraction ND Reiter, J Runge, A Gerhardus EGU General Assembly Conference Abstracts, EGU22-9112, 2022 | | 2022 |
| Reliable causal discovery in time series A Gerhardus | | 2022 |
Jakob RungeGerman Aerospace Center and TU BerlinBestätigte E-Mail-Adresse bei dlr.de
