| Detection of neuron membranes in electron microscopy images using a serial neural network architecture E Jurrus, ARC Paiva, S Watanabe, JR Anderson, BW Jones, RT Whitaker, ... Medical image analysis 14 (6), 770-783, 2010 | 132 | 2010 |
| A reproducing kernel Hilbert space framework for spike train signal processing ARC Paiva, I Park, JC Principe Neural computation 21 (2), 424-449, 2009 | 116 | 2009 |
| Fault detection and identification using Bayesian recurrent neural networks W Sun, ARC Paiva, P Xu, A Sundaram, RD Braatz Computers & Chemical Engineering 141, 106991, 2020 | 114 | 2020 |
| A reproducing kernel Hilbert space framework for information-theoretic learning JW Xu, ARC Paiva, I Park, JC Principe IEEE Transactions on Signal Processing 56 (12), 5891-5902, 2008 | 89 | 2008 |
| A comparison of binless spike train measures ARC Paiva, I Park, JC Príncipe Neural Computing and Applications 19, 405-419, 2010 | 88 | 2010 |
| Kernel methods on spike train space for neuroscience: a tutorial IM Park, S Seth, ARC Paiva, L Li, JC Principe IEEE Signal Processing Magazine 30 (4), 149-160, 2013 | 78 | 2013 |
| Sequential Monte Carlo point-process estimation of kinematics from neural spiking activity for brain-machine interfaces Y Wang, ARC Paiva, JC Príncipe, JC Sanchez Neural computation 21 (10), 2894-2930, 2009 | 50 | 2009 |
| Characterizing datasets using sampling, weighting, and approximation of an eigendecomposition AR Paiva, T Tasdizen US Patent 8,412,651, 2013 | 44 | 2013 |
| Determining well parameters for optimization of well performance DN Burch, ARC Paiva, R van den Bosch US Patent 9,946,974, 2018 | 40 | 2018 |
| Seismic stratigraphic surface classification LA Wahrmund, ARC Paiva, SE Hanson-Hedgecock US Patent 10,139,507, 2018 | 35 | 2018 |
| Nonlinear component analysis based on correntropy JW Xu, PP Pokharel, ARC Paiva, JC Príncipe The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 33 | 2006 |
| Semi-automated neuron boundary detection and nonbranching process segmentation in electron microscopy images E Jurrus, S Watanabe, RJ Giuly, ARC Paiva, MH Ellisman, EM Jorgensen, ... Neuroinformatics 11, 5-29, 2013 | 32 | 2013 |
| Inner products for representation and learning in the spike train domain ARC Paiva, I Park, JC Principe Statistical signal processing for neuroscience and neurotechnology, 265-309, 2010 | 28 | 2010 |
| Fast adaboost training using weighted novelty selection M Seyedhosseini, ARC Paiva, T Tasdizen The 2011 International Joint Conference on Neural Networks, 1245-1250, 2011 | 27 | 2011 |
| On the use of standards for microarray lossless image compression AJ Pinho, ARC Paiva, AJR Neves IEEE transactions on biomedical engineering 53 (3), 563-566, 2006 | 26 | 2006 |
| Automatic markup of neural cell membranes using boosted decision stumps KU Venkataraju, ARC Paiva, E Jurrus, T Tasdizen 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2009 | 25 | 2009 |
| Advancing from predictive maintenance to intelligent maintenance with ai and iiot H Zheng, AR Paiva, CS Gurciullo arXiv preprint arXiv:2009.00351, 2020 | 20 | 2020 |
| An efficient algorithm for continuous time cross correlogram of spike trains I Park, ARC Paiva, TB DeMarse, JC Príncipe Journal of Neuroscience methods 168 (2), 514-523, 2008 | 16 | 2008 |
| Self-organizing maps with dynamic learning for signal reconstruction J Cho, ARC Paiva, SP Kim, JC Sanchez, JC Príncipe Neural Networks 20 (2), 274-284, 2007 | 15 | 2007 |
| A Monte Carlo sequential estimation for point process optimum filtering Y Wang, ARC Paiva, JC Príncipe The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 15 | 2006 |
jose principeprofessor of ECE, U. of FloridaVerified email at cnel.ufl.edu