Causal inference through the structural causal marginal problem L Gresele, J Von Kügelgen, J Kübler, E Kirschbaum, B Schölkopf, ...
International Conference on Machine Learning, 7793-7824, 2022
29 2022 Sparse convolutional coding for neuronal assembly detection S Peter, E Kirschbaum, M Both, L Campbell, B Harvey, C Heins, ...
Advances in Neural Information Processing Systems 30, 2017
27 2017 Disco: deep learning, instance segmentation, and correlations for cell segmentation in calcium imaging E Kirschbaum, A Bailoni, FA Hamprecht
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
21 2020 LeMoNADe: Learned motif and neuronal assembly detection in calcium imaging videos E Kirschbaum, M Haußmann, S Wolf, H Sonntag, J Schneider, S Elzoheiry, ...
arXiv preprint arXiv:1806.09963, 2018
14 2018 Obtaining causal information by merging datasets with maxent SHG Mejia, E Kirschbaum, D Janzing
International Conference on Artificial Intelligence and Statistics, 581-603, 2022
11 2022 DISCo for the CIA: deep learning, instance segmentation, and correlations for calcium imaging analysis E Kirschbaum, A Bailoni, FA Hamprecht
Preprint at https://arxiv. org/abs/1908.07957 v4, 2020
3 2020 DISCo: Deep learning, Instance Segmentation, and Correlations for cell segmentation in calcium imaging E Kirschbaum, A Bailoni, FA Hamprecht
arXiv preprint arXiv:1908.07957, 2019
3 2019 The PetShop Dataset--Finding Causes of Performance Issues across Microservices M Hardt, WR Orchard, P Blöbaum, S Kasiviswanathan, E Kirschbaum
arXiv preprint arXiv:2311.04806, 2023
1 2023 Beyond Single-Feature Importance with ICECREAM M Oesterle, P Blöbaum, AA Mastakouri, E Kirschbaum
arXiv preprint arXiv:2307.09779, 2023
1 2023 -calibration of Language Model Confidence Scores for Generative QAP Manggala, A Mastakouri, E Kirschbaum, SP Kasiviswanathan, ...
arXiv preprint arXiv:2410.06615, 2024
2024 Estimating Joint interventional distributions from marginal interventional data SHG Mejia, E Kirschbaum, A Kekić, A Mastakouri
arXiv preprint arXiv:2409.01794, 2024
2024 Estimating Joint interventional distributions from marginal interventional data S Hernan Garrido Mejia, E Kirschbaum, A Kekić, A Mastakouri
arXiv e-prints, arXiv: 2409.01794, 2024
2024 Score matching through the roof: linear, nonlinear, and latent variables causal discovery F Montagna, PM Faller, P Bloebaum, E Kirschbaum, F Locatello
arXiv preprint arXiv:2407.18755, 2024
2024 Obtaining Causal Information by Merging Datasets with MAXENT S Hernan Garrido Mejia, E Kirschbaum, D Janzing
arXiv e-prints, arXiv: 2107.07640, 2021
2021