| International crop trade networks: the impact of shocks and cascades R Burkholz, F Schweitzer Environmental research letters 14 (11), 114013, 2019 | 98 | 2019 |
| GRAND: a database of gene regulatory network models across human conditions M Ben Guebila, CM Lopes-Ramos, D Weighill, AR Sonawane, R Burkholz, ... Nucleic Acids Research 50 (D1), D610-D621, 2022 | 92 | 2022 |
| Assessment of artificial intelligence in echocardiography diagnostics in differentiating takotsubo syndrome from myocardial infarction F Laumer, D Di Vece, VL Cammann, M Würdinger, V Petkova, ... JAMA cardiology 7 (5), 494-503, 2022 | 85 | 2022 |
| Glycowork: A Python package for glycan data science and machine learning L Thomès, R Burkholz, D Bojar Glycobiology 31 (10), 1240-1244, 2021 | 56 | 2021 |
| Using graph convolutional neural networks to learn a representation for glycans R Burkholz, J Quackenbush, D Bojar Cell Reports 35 (11), 2021 | 54 | 2021 |
| Systemic risk in multiplex networks with asymmetric coupling and threshold feedback R Burkholz, MV Leduc, A Garas, F Schweitzer Physica D: Nonlinear Phenomena 323, 64-72, 2016 | 49 | 2016 |
| On the existence of universal lottery tickets R Burkholz, N Laha, R Mukherjee, A Gotovos ICLR 2022, 2021 | 48 | 2021 |
| Initialization of relus for dynamical isometry R Burkholz, A Dubatovka NeurIPS 2019, 2019 | 44 | 2019 |
| Why random pruning is all we need to start sparse AH Gadhikar, S Mukherjee, R Burkholz International Conference on Machine Learning, 10542-10570, 2023 | 40 | 2023 |
| How damage diversification can reduce systemic risk R Burkholz, A Garas, F Schweitzer Physical Review E 93 (4), 042313, 2016 | 38 | 2016 |
| The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks M Ben Guebila, T Wang, CM Lopes-Ramos, V Fanfani, D Weighill, ... Genome Biology 24 (1), 45, 2023 | 37 | 2023 |
| Biologically informed NeuralODEs for genome-wide regulatory dynamics I Hossain, V Fanfani, J Fischer, J Quackenbush, R Burkholz Genome Biology 25 (1), 127, 2024 | 33 | 2024 |
| Gene Regulatory Network Inference as Relaxed Graph Matching D Weighill, MB Guebila, C Lopes-Ramos, K Glass, J Quackenbush, ... AAAI 2021, 2020 | 30 | 2020 |
| Most Activation Functions Can Win the Lottery Without Excessive Depth R Burkholz NeurIPS 2022, 2022 | 29 | 2022 |
| Plant'n'Seek: Can You Find the Winning Ticket? J Fischer, R Burkholz ICLR 2022, 2021 | 27 | 2021 |
| Improving 1-year mortality prediction in ACS patients using machine learning S Weichwald, A Candreva, R Burkholz, R Klingenberg, L Räber, D Heg, ... European Heart Journal Acute Cardiovascular Care 10 (8), 855-865, 2021 | 26 | 2021 |
| DRAGON: determining regulatory associations using graphical models on multi-omic networks KH Shutta, D Weighill, R Burkholz, MB Guebila, DL DeMeo, HU Zacharias, ... Nucleic Acids Research 51, 2023 | 25* | 2023 |
| Convolutional and Residual Networks Provably Contain Lottery Tickets R Burkholz ICML 2022, 2022 | 23 | 2022 |
| Explicit size distributions of failure cascades redefine systemic risk on finite networks R Burkholz, HJ Herrmann, F Schweitzer Scientific reports 8 (1), 6878, 2018 | 21 | 2018 |
| Lottery tickets with nonzero biases J Fischer, A Gadhikar, R Burkholz arXiv preprint arXiv:2110.11150, 2021 | 20 | 2021 |
John QuackenbushHarvard T.H. Chan School of Public Health, Channing Division of Network Medicine, and Dana-FarberVerified email at hsph.harvard.edu
