| Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation RM Silva, L Baroni, RS Ferreira, D Civitarese, D Szwarcman, EV Brazil arXiv preprint arXiv:1904.00770, 2019 | 60 | 2019 |
| Seismic facies segmentation using deep learning D Chevitarese, D Szwarcman, RMD Silva, EV Brazil AAPG Annual and Exhibition, 2018 | 41 | 2018 |
| Deep learning applied to seismic facies classification: A methodology for training DS Chevitarese, D Szwarcman, RMG e Silva, EV Brazil Saint Petersburg 2018 2018 (1), 1-5, 2018 | 36 | 2018 |
| Efficient classification of seismic textures DS Chevitarese, D Szwarcman, EV Brazil, B Zadrozny 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 33 | 2018 |
| Quantum-Inspired Neural Architecture Search D Szwarcman, D Civitarese, M Vellasco 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 29 | 2019 |
| Semantic Segmentation of Seismic Images D Civitarese, D Szwarcman, EV Brazil, B Zadrozny arXiv preprint arXiv:1905.04307, 2019 | 29 | 2019 |
| Generating physically-consistent high-resolution climate data with hard-constrained neural networks P Harder, Q Yang, V Ramesh, P Sattigeri, A Hernandez-Garcia, C Watson, ... arXiv preprint arXiv:2208.05424 18, 109-122, 2022 | 22 | 2022 |
| Transfer learning applied to seismic images classification D Chevitarese, D Szwarcman, RMD Silva, EV Brazil AAPG Annual and Exhibition, 2018 | 22 | 2018 |
| Quantum-inspired evolutionary algorithm applied to neural architecture search D Szwarcman, D Civitarese, M Vellasco Applied Soft Computing 120, 108674, 2022 | 19 | 2022 |
| Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network DS Civitarese, D Szwarcman, B Zadrozny, C Watson arXiv preprint arXiv:2107.06846, 2021 | 18 | 2021 |
| Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling Q Yang, A Hernandez-Garcia, P Harder, V Ramesh, P Sattegeri, ... arXiv preprint arXiv:2305.14452, 2023 | 15 | 2023 |
| Hard-Constrained Deep Learning for Climate Downscaling P Harder, A Hernandez-Garcia, V Ramesh, Q Yang, P Sattegeri, ... Journal of Machine Learning Research 24 (365), 1-40, 2023 | 12 | 2023 |
| Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation L Baroni, RM Silva, RS Ferreira, D Civitarese, D Szwarcman, EV Brazil arXiv preprint arXiv:1903.12060, 2019 | 10 | 2019 |
| Netherlands dataset: A new public dataset for machine learning in seismic interpretation: arXiv preprint, doi: 10.48550 RM Silva, L Baroni, RS Ferreira, D Civitarese, D Szwarcman, EV Brazil arXiv, 1904 | 8 | 1904 |
| Quantifying milk proteins using infrared photodetection for portable equipment D Szwarcman, GM Penello, RMS Kawabata, MP Pires, PL Souza Journal of Food Engineering 308, 110676, 2021 | 7 | 2021 |
| Enabling Robust Horizon Picking From Small Training Sets AB Mattos, D Civitarese, D Szwarcman, M Oliveira, S Zaytsev, DG Semin, ... IEEE Transactions on Geoscience and Remote Sensing 59 (6), 5317-5324, 2020 | 7 | 2020 |
| Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network, arXiv DS Civitarese, D Szwarcman, B Zadrozny, C Watson arXiv preprint arXiv:2107.06846, 2021 | 5 | 2021 |
| Vacuum Ultraviolet Laser Induced Breakdown Spectroscopy (VUV-LIBS) with machine learning for pharmaceutical analysis MB Alli, D Szwarcman, DS Civitarese, P Hayden Journal of Physics: Conference Series 1289 (1), 012031, 2019 | 5 | 2019 |
| A modular framework for extreme weather generation B Zadrozny, CD Watson, D Szwarcman, D Civitarese, D Oliveira, ... arXiv preprint arXiv:2102.04534, 2021 | 4 | 2021 |
| A cyclic learning approach for improving pre-stack seismic processing DAB Oliveira, D Szwarcman, R da Silva Ferreira, S Zaytsev, D Semin Scientific Reports 11 (1), 1-13, 2021 | 3 | 2021 |
Daniel Salles CivitareseIBM ResearchDirección de correo verificada de br.ibm.com
