| Towards automated machine learning: Evaluation and comparison of AutoML approaches and tools A Truong, A Walters, J Goodsitt, K Hines, CB Bruss, R Farivar 2019 IEEE 31st international conference on tools with artificial …, 2019 | 251 | 2019 |
| Saint: Improved neural networks for tabular data via row attention and contrastive pre-training G Somepalli, M Goldblum, A Schwarzschild, CB Bruss, T Goldstein arXiv preprint arXiv:2106.01342, 2021 | 196 | 2021 |
| Culture and getting to yes: The linguistic signature of creative agreements in the United States and Egypt MJ Gelfand, L Severance, T Lee, CB Bruss, J Lun, AH Abdel‐Latif, ... Journal of Organizational Behavior 36 (7), 967-989, 2015 | 63 | 2015 |
| Deeptrax: Embedding graphs of financial transactions A Khazane, J Rider, M Serpe, A Gogoglou, K Hines, CB Bruss, R Serpe 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 59 | 2019 |
| The cultural contagion of conflict M Gelfand, G Shteynberg, T Lee, J Lun, S Lyons, C Bell, JY Chiao, ... Philosophical Transactions of the Royal Society B: Biological Sciences 367 …, 2012 | 57 | 2012 |
| Route planning system and methodology which account for safety factors PJ Ehsani, CB Bruss, JK Khodadad US Patent App. 14/205,495, 2015 | 39 | 2015 |
| Systems and methods of detecting email-based attacks through machine learning CB Bruss, S Fletcher, L Yu, J Kressel US Patent 10,397,272, 2019 | 38 | 2019 |
| Critical assessment of the foundations of power transmission and distribution reliability metrics and standards R Nateghi, SD Guikema, Y Wu, CB Bruss Risk analysis 36 (1), 4-15, 2016 | 31 | 2016 |
| Latent-cf: a simple baseline for reverse counterfactual explanations R Balasubramanian, S Sharpe, B Barr, J Wittenbach, CB Bruss arXiv preprint arXiv:2012.09301, 2020 | 24 | 2020 |
| Transfer learning with deep tabular models R Levin, V Cherepanova, A Schwarzschild, A Bansal, CB Bruss, ... arXiv preprint arXiv:2206.15306, 2022 | 22 | 2022 |
| Systems and methods of detecting email-based attacks through machine learning CB Bruss, S Fletcher, L Yu, J Kressel US Patent 10,805,347, 2020 | 22 | 2020 |
| GOAT: A global transformer on large-scale graphs K Kong, J Chen, J Kirchenbauer, R Ni, CB Bruss, T Goldstein International Conference on Machine Learning, 17375-17390, 2023 | 15 | 2023 |
| Neural embeddings of transaction data C Bruss, K Hines US Patent 10,789,530, 2020 | 14 | 2020 |
| Based-xai: breaking ablation studies down for explainable artificial intelligence I Hameed, S Sharpe, D Barcklow, J Au-Yeung, S Verma, J Huang, B Barr, ... arXiv preprint arXiv:2207.05566, 2022 | 11 | 2022 |
| On the interpretability and evaluation of graph representation learning A Gogoglou, CB Bruss, KE Hines arXiv preprint arXiv:1910.03081, 2019 | 10 | 2019 |
| Counterfactual explanations via latent space projection and interpolation B Barr, MR Harrington, S Sharpe, CB Bruss arXiv preprint arXiv:2112.00890, 2021 | 9 | 2021 |
| Towards ground truth explainability on tabular data B Barr, K Xu, C Silva, E Bertini, R Reilly, CB Bruss, JD Wittenbach arXiv preprint arXiv:2007.10532, 2020 | 9 | 2020 |
| Explaining national trends in terrestrial water storage CB Bruss, R Nateghi, BF Zaitchik Frontiers in Environmental Science 7, 85, 2019 | 8 | 2019 |
| Identifying interpretable subspaces in image representations N Kalibhat, S Bhardwaj, CB Bruss, H Firooz, M Sanjabi, S Feizi International Conference on Machine Learning, 15623-15638, 2023 | 5 | 2023 |
| MetaBalance: high-performance neural networks for class-imbalanced data A Bansal, M Goldblum, V Cherepanova, A Schwarzschild, CB Bruss, ... arXiv preprint arXiv:2106.09643, 2021 | 5 | 2021 |
