| Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning CJ Reed, R Gupta, S Li, S Brockman, C Funk, B Clipp, K Keutzer, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 77 | 2023 |
| Offline contextual bandits with high probability fairness guarantees B Metevier, S Giguere, S Brockman, A Kobren, Y Brun, E Brunskill, ... Advances in neural information processing systems 32, 2019 | 55 | 2019 |
| Automated business process discovery from unstructured natural-language documents AJ Chambers, AM Stringfellow, BB Luo, SJ Underwood, TG Allard, ... Business Process Management Workshops: BPM 2020 International Workshops …, 2020 | 20 | 2020 |
| Toward quantifying the real-versus-synthetic imagery training data reality gap: analysis and practical applications CN Reinhardt, S Brockman, R Blue, B Clipp, A Hoogs Synthetic Data for Artificial Intelligence and Machine Learning: Tools …, 2024 | | 2024 |
| Creating Deep Learning Detectors in VIAME for Rare Objects in Marine Imagery A Hoogs, A Lynch, S Brockman, C Funk, B Ravichandran, MD Dawkins 2024 Ocean Sciences Meeting, 2024 | | 2024 |
| Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning R Gupta, S Li, S Brockman, C Funk, B Clipp, K Keutzer, S Candido, ... AGU23, 2023 | | 2023 |
| Automated Business Process Discovery from Unstructured Natural-Language Documents L Shing, A Wollaber, C VanDam Business Process Management Workshops: BPM 2020 International Workshops …, 2021 | | 2021 |
