| 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 | 94 | 2020 |
| 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 | 71 | 2023 |
| 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 | 52 | 2016 |
| Quantum periods of Calabi–Yau fourfolds A Gerhardus, H Jockers Nuclear Physics B 913, 425-474, 2016 | 40 | 2016 |
| Discovering causal relations and equations from data G Camps-Valls, A Gerhardus, U Ninad, G Varando, G Martius, ... Physics Reports 1044, 1-68, 2023 | 35 | 2023 |
| 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 | 26 | 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 | 10 | 2021 |
| 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 | 7 | 2022 |
| Characterization of causal ancestral graphs for time series with latent confounders A Gerhardus The Annals of Statistics 52 (1), 103-130, 2024 | 4 | 2024 |
| 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 | 3 | 2023 |
| 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 | 2 | 2023 |
| Causal inference on process graphs, part II: Causal structure and effect identification ND Reiter, J Wahl, A Gerhardus, J Runge arXiv preprint arXiv:2406.17422, 2024 | 1 | 2024 |
| 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 | 1 | 2024 |
| 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 | 1 | 2023 |
| 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 |
| Causal discovery in ensembles of climate time series A Gerhardus, J Runge EGU General Assembly Conference Abstracts, EGU22-6958, 2022 | 1 | 2022 |
| String Compactifications from the Worldsheet and Target Space Point of View A Gerhardus Universitäts-und Landesbibliothek Bonn, 2019 | 1 | 2019 |
| 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 |
Jakob RungeTU Dresden在 tu-dresden.de 的电子邮件经过验证
