| 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 | 38 | 2019 |
| Deep learning applied to seismic facies classification: A methodology for training DS Chevitarese, D Szwarcman, RM Gama e Silva, E Vital Brazil Saint Petersburg 2018 2018 (1), 1-5, 2018 | 30 | 2018 |
| Seismic facies segmentation using deep learning D Chevitarese, D Szwarcman, RMD Silva, EV Brazil AAPG Annual and Exhibition, 2018 | 27 | 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 | 24 | 2018 |
| Semantic Segmentation of Seismic Images D Civitarese, D Szwarcman, EV Brazil, B Zadrozny arXiv preprint arXiv:1905.04307, 2019 | 20 | 2019 |
| Quantum-Inspired Neural Architecture Search D Szwarcman, D Civitarese, M Vellasco 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 18 | 2019 |
| Transfer learning applied to seismic images classification D Chevitarese, D Szwarcman, RMD Silva, EV Brazil AAPG Annual and Exhibition, 2018 | 16 | 2018 |
| Quantum-inspired evolutionary algorithm applied to neural architecture search D Szwarcman, D Civitarese, M Vellasco Applied Soft Computing 120, 108674, 2022 | 7 | 2022 |
| Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network DS Civitarese, D Szwarcman, B Zadrozny, C Watson arXiv preprint arXiv:2107.06846, 2021 | 6 | 2021 |
| 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 | 5 | 2021 |
| 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 | 5 | 2019 |
| 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 |
| 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 | 3 | 2020 |
| Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency D Szwarcman, D Civitarese, M Vellasco 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 509-514, 2019 | 3 | 2019 |
| 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 | 3 | 2019 |
| Ore content estimation based on spatial geological data through 3D convolutional neural networks BW WSR Carvalho, D Civitarese, D Szwarcman, P Cavalin, B Zadrozny, ... 81st EAGE Conference and Exhibition 2019 Workshop Programme 2019 (1), 1-5, 2019 | 3 | 2019 |
| Stratigraphic Segmentation Using Convolutional Neural Networks D Civitarese, D Szwarcman, E Vital Brazil 81st EAGE Conference and Exhibition 2019 Workshop Programme 2019 (1), 1-5, 2019 | 3 | 2019 |
| A modular framework for extreme weather generation B Zadrozny, CD Watson, D Szwarcman, D Civitarese, D Oliveira, ... arXiv preprint arXiv:2102.04534, 2021 | 2 | 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 | | 2023 |
| Physics-Constrained Deep Learning for Downscaling P Harder, V Ramesh, A Hernandez-Garcia, Q Yang, P Sattigeri, ... EGU23, 2023 | | 2023 |
Daniel Salles CivitareseIBM ResearchVerified email at br.ibm.com
