| Simplicial Neural Networks S Ebli, M Defferrard, G Spreemann arXiv preprint arXiv:2010.03633, 2020 | 120 | 2020 |
| Approximating persistent homology in Euclidean space through collapses MB Botnan, G Spreemann Applicable Algebra in Engineering, Communication and Computing 26 (1-2), 73-101, 2015 | 47 | 2015 |
| Topological exploration of artificial neuronal network dynamics JB Bardin, G Spreemann, K Hess Network Neuroscience 3 (3), 725-743, 2019 | 27 | 2019 |
| Topology of Learning in Artificial Neural Networks M Gabella, N Afambo, S Ebli, G Spreemann arXiv preprint arXiv:1902.08160, 2019 | 21* | 2019 |
| A Notion of Harmonic Clustering in Simplicial Complexes S Ebli, G Spreemann 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 18 | 2019 |
| Same but different: Distance correlations between topological summaries K Turner, G Spreemann Topological Data Analysis: The Abel Symposium 2018, 459-490, 2020 | 17 | 2020 |
| Dynamics of CLIMP-63 S-acylation control ER morphology PA Sandoz, RA Denhardt-Eriksson, L Abrami, LA Abriata, G Spreemann, ... Nature Communications 14 (1), 264, 2023 | 16* | 2023 |
| Using persistent homology to reveal hidden information in neural data G Spreemann, B Dunn, MB Botnan, NA Baas arXiv preprint arXiv:1510.06629, 2015 | 13 | 2015 |
| Using persistent homology to reveal hidden covariates in systems governed by the kinetic Ising model G Spreemann, B Dunn, MB Botnan, NA Baas Physical Review E 97 (3), 032313, 2018 | 11 | 2018 |
| Intact Drosophila central nervous system cellular quantitation reveals sexual dimorphism W Jiao, G Spreemann, E Ruchti, S Banerjee, S Vernon, Y Shi, RS Stowers, ... Elife 11, e74968, 2022 | 4 | 2022 |
| FORLORN: A Framework for Comparing Offline Methods and Reinforcement Learning for Optimization of RAN Parameters V Edvardsen, G Spreemann, JV Abeele arXiv preprint arXiv:2209.13540, 2022 | 1 | 2022 |
