| Deep learning in spiking neural networks A Tavanaei, M Ghodrati, SR Kheradpisheh, T Masquelier, A Maida Neural networks 111, 47-63, 2019 | 1345 | 2019 |
| BP-STDP: Approximating backpropagation using spike timing dependent plasticity A Tavanaei, A Maida Neurocomputing 330, 39-47, 2019 | 241 | 2019 |
| A novel data-driven model for real-time influenza forecasting SR Venna, A Tavanaei, RN Gottumukkala, VV Raghavan, AS Maida, ... Ieee Access 7, 7691-7701, 2018 | 143 | 2018 |
| Multi-layer unsupervised learning in a spiking convolutional neural network A Tavanaei, AS Maida 2017 international joint conference on neural networks (IJCNN), 2023-2030, 2017 | 88 | 2017 |
| Bio-inspired spiking convolutional neural network using layer-wise sparse coding and STDP learning A Tavanaei, AS Maida arXiv preprint arXiv:1611.03000, 2016 | 80 | 2016 |
| A spiking network that learns to extract spike signatures from speech signals A Tavanaei, AS Maida Neurocomputing 240, 191-199, 2017 | 65 | 2017 |
| Bio-inspired multi-layer spiking neural network extracts discriminative features from speech signals A Tavanaei, A Maida Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 61 | 2017 |
| Training spiking convnets by stdp and gradient descent A Tavanaei, Z Kirby, AS Maida 2018 international joint conference on neural networks (IJCNN), 1-8, 2018 | 57 | 2018 |
| Acquisition of visual features through probabilistic spike-timing-dependent plasticity A Tavanaei, T Masquelier, AS Maida 2016 International Joint Conference on Neural Networks (IJCNN), 307-314, 2016 | 55 | 2016 |
| Embedded Encoder-Decoder in Convolutional Networks Towards Explainable AI A Tavanaei Arxiv, 2020 | 35 | 2020 |
| Representation learning using event-based STDP A Tavanaei, T Masquelier, A Maida Neural Networks 105, 294-303, 2018 | 35 | 2018 |
| A minimal spiking neural network to rapidly train and classify handwritten digits in binary and 10-digit tasks A Tavanaei, AS Maida Int. J. Adv. Res. Artif. Intell 4 (7), 1-8, 2015 | 34 | 2015 |
| Profiling drilling fluid’s invasion using scanning electron microscopy: implications for bridging and wellbore strengthening effects S Salehi, S Hussmann, M Karimi, C Ezeakacha, A Tavanaei SPE Deepwater Drilling and Completions Conference, D021S009R004, 2014 | 30 | 2014 |
| Training a hidden Markov model with a Bayesian spiking neural network A Tavanaei, AS Maida Journal of Signal Processing Systems 90, 211-220, 2018 | 29 | 2018 |
| Pore, throat, and grain detection for rock sem images using digitalwatershed image segmentation algorithm A Tavanaei, S Salehi Journal of Porous Media 18 (5), 2015 | 28 | 2015 |
| Towards recognition of protein function based on its structure using deep convolutional networks A Tavanaei, AS Maida, A Kaniymattam, R Loganantharaj 2016 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2016 | 20 | 2016 |
| A deep learning model for predicting tumor suppressor genes and oncogenes from PDB structure A Tavanaei, N Anandanadarajah, A Maida, R Loganantharaj 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2017 | 19 | 2017 |
| Post frac gas production through shale capillary activation A Hayatdavoudi, MA Boamah, A Tavnaei, KG Sawant, F Boukadi SPE Oklahoma City Oil and Gas Symposium/Production and Operations Symposium …, 2015 | 15 | 2015 |
| Mel-scaled discrete wavelet transform and dynamic features for the Persian phoneme recognition A Tavanaei, MT Manzuri, H Sameti 2011 international symposium on artificial intelligence and signal …, 2011 | 13 | 2011 |
| Unsupervised learning to rank aggregation using parameterized function optimization A Tavanaei, R Gottumukkalay, AS Maida, VV Raghavan 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 7 | 2018 |
Anthony S. MaidaSchool of Computing and Informatics, UL Lafayette在 louisiana.edu 的电子邮件经过验证
