| Phi-3 technical report: A highly capable language model locally on your phone M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... arXiv preprint arXiv:2404.14219, 2024 | 975 | 2024 |
| Textbooks are all you need S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ... arXiv preprint arXiv:2306.11644, 2023 | 612 | 2023 |
| Deep learning-aided Parkinson's disease diagnosis from handwritten dynamics CR Pereira, SAT Weber, C Hook, GH Rosa, JP Papa 2016 29th SIBGRAPI conference on graphics, patterns and images (SIBGRAPI …, 2016 | 286 | 2016 |
| Phi-2: The surprising power of small language models M Javaheripi, S Bubeck, M Abdin, J Aneja, S Bubeck, CCT Mendes, ... Microsoft Research Blog 1 (3), 3, 2023 | 225 | 2023 |
| Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification CR Pereira, DR Pereira, GH Rosa, VHC Albuquerque, SAT Weber, ... Artificial intelligence in medicine 87, 67-77, 2018 | 206 | 2018 |
| A recurrence plot-based approach for Parkinson’s disease identification LCS Afonso, GH Rosa, CR Pereira, SAT Weber, C Hook, ... Future Generation Computer Systems 94, 282-292, 2019 | 128 | 2019 |
| A survey on text generation using generative adversarial networks GH De Rosa, JP Papa Pattern Recognition 119, 108098, 2021 | 127 | 2021 |
| Soft-Tempering Deep Belief Networks Parameters Through Genetic Programming GH de Rosa, JP Papa Journal of Artificial Intelligence and Systems 1 (1), 43-59, 2019 | 115 | 2019 |
| Convolutional neural networks applied for Parkinson’s disease identification CR Pereira, DR Pereira, JP Papa, GH Rosa, XS Yang Machine Learning for Health Informatics: State-Of-The-Art and Future …, 2016 | 89 | 2016 |
| Fine-tuning convolutional neural networks using harmony search G Rosa, J Papa, A Marana, W Scheirer, D Cox Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2015 | 71 | 2015 |
| Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques JP Papa, GH Rosa, AN Marana, W Scheirer, DD Cox Journal of Computational Science 9, 14-18, 2015 | 62 | 2015 |
| Handling dropout probability estimation in convolution neural networks using meta-heuristics GH De Rosa, JP Papa, XS Yang Soft Computing 22, 6147-6156, 2018 | 59 | 2018 |
| Learning parameters in deep belief networks through firefly algorithm G Rosa, J Papa, K Costa, L Passos, C Pereira, XS Yang Artificial Neural Networks in Pattern Recognition: 7th IAPR TC3 Workshop …, 2016 | 57 | 2016 |
| Phi-4 technical report M Abdin, J Aneja, H Behl, S Bubeck, R Eldan, S Gunasekar, M Harrison, ... arXiv preprint arXiv:2412.08905, 2024 | 53 | 2024 |
| Feature selection through binary brain storm optimization JP Papa, GH Rosa, AN de Souza, LCS Afonso Computers & Electrical Engineering 72, 468-481, 2018 | 46 | 2018 |
| On the model selection of bernoulli restricted boltzmann machines through harmony search JP Papa, GH Rosa, KA Costa, NA Marana, W Scheirer, DD Cox Proceedings of the companion publication of the 2015 annual conference on …, 2015 | 41 | 2015 |
| Stroke lesion detection using convolutional neural networks DR Pereira, PP Reboucas Filho, GH de Rosa, JP Papa, ... 2018 International joint conference on neural networks (IJCNN), 1-6, 2018 | 39 | 2018 |
| Quaternion-based deep belief networks fine-tuning JP Papa, GH Rosa, DR Pereira, XS Yang Applied Soft Computing 60, 328-335, 2017 | 37 | 2017 |
| Litetransformersearch: Training-free on-device search for efficient autoregressive language models M Javaheripi, S Shah, S Mukherjee, TL Religa, CCT Mendes, ... First Conference on Automated Machine Learning (Late-Breaking Workshop), 2022 | 23 | 2022 |
| Adaptive improved flower pollination algorithm for global optimization D Rodrigues, GH de Rosa, LA Passos, JP Papa Nature-inspired computation in data mining and machine learning, 1-21, 2019 | 23 | 2019 |
João Paulo PapaFull Professor, SMIEEE, FIAPR, FAAIA, FAvH, São Paulo State UniversityEmail confirmado em unesp.br