| 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 | 150 | 2023 |
| 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 | 124 | 2020 |
| Discovering causal relations and equations from data G Camps-Valls, A Gerhardus, U Ninad, G Varando, G Martius, ... Physics Reports 1044, 1-68, 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 | 59 | 2016 |
| Quantum periods of Calabi–Yau fourfolds A Gerhardus, H Jockers Nuclear Physics B 913, 425-474, 2016 | 42 | 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 | 27 | 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 |
| 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 | 14 | 2022 |
| 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 | 11 | 2021 |
| Characterization of causal ancestral graphs for time series with latent confounders A Gerhardus The Annals of Statistics 52 (1), 103-130, 2024 | 8 | 2024 |
| 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 | 7 | 2023 |
| 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 | 5 | 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 | 5 | 2023 |
| Causal inference for temporal patterns ND Reiter, A Gerhardus, J Runge arXiv preprint arXiv:2205.15149, 2022 | 2 | 2022 |
| Causal discovery with endogenous context variables W Günther, OI Popescu, M Rabel, U Ninad, A Gerhardus, J Runge arXiv preprint arXiv:2412.04981, 2024 | 1 | 2024 |
| Triangulation for causal loop diagrams: constructing biopsychosocial models using group model building, literature review, and causal discovery JF Uleman, M Luijten, WF Abdo, J Vyrastekova, A Gerhardus, J Runge, ... npj Complexity 1 (1), 19, 2024 | 1 | 2024 |
| Causal modeling in multi-context systems: Distinguishing multiple context-specific causal graphs which account for observational support M Rabel, W Günther, J Runge, A Gerhardus arXiv preprint arXiv:2410.20405, 2024 | 1 | 2024 |
| 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 |
| A global Markov property for solutions of stochastic difference equations and the corresponding full time graphs T Hochsprung, J Runge, A Gerhardus 40th Conference on Uncertainty in Artificial Intelligence 244, 1698-1726, 2024 | 1 | 2024 |
| 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 | 1 | 2023 |
Jakob RungeTU Dresden / ScaDS.AIDirección de correo verificada de tu-dresden.de
