- Sequential Monte Carlo Point Process Estimation of Kinematics from Neural Spiking Activity for Brain Machine Interfaces
- Spectral Clustering of Synchronous Spike Trains 1 Spectral Clustering of Synchronous
- Fast AdaBoost Training using Weighted Novelty Selection Mojtaba Seyedhosseini1,2, Antonio R. C. Paiva1 and Tolga Tasdizen1,2
- Serial Neural Network Classifier for Membrane Detection using a Filter Bank.
- WORKSHOP ON MICROSCOPIC IMAGE ANALYSIS WITH APPLICATIONS IN BIOLOGY, SEPTEMBER 2009 1 Serial Neural Network Classifier for Membrane
- A Reproducing Kernel Hilbert Space framework for Spike Train Signal Processing
- Optimization in Reproducing kernel Hilbert Spaces of Spike Trains
- Using Sequential Context for Image Analysis Antonio R. C. Paiva1, Elizabeth Jurrus1,2 and Tolga Tasdizen1,3
- Image Parsing with a Three-State Series Neural Network Classifier Mojtaba Seyedhosseini1,2, Antonio R. C. Paiva1 and Tolga Tasdizen1,2
- Detection of neuron membranes in electron microscopy images using a serial neural network architecture
- A Monte Carlo Sequential Estimation for Point Process Optimum Filtering
- REPRODUCING KERNEL HILBERT SPACES FOR POINT PROCESSES, WITH APPLICATIONS TO NEURAL ACTIVITY ANALYSIS
- A Closed Form Solution for Multiple-Input Spike Based Adaptive Il Park, Antonio R. C. Paiva, Jose C. Principe and John G. Harris
- Kernel Principal Components Are Maximum Entropy Projections
- Abstract--The previous decoding algorithms for Brain Machine Interfaces are normally utilized to estimate animal's
- "A reproducing kernel Hilbert space framework for Information-Theoretic Learning," chapter 9, Jose C. Principe, Jianwu Xu, Robert Jenssen, Antonio R. C. Paiva, Il Park
- Evaluation of some reordering techniques for image VQ index compression
- Hierarchal Decomposition of Neural Data using Boosted Mixtures of Hidden Markov Chains and its application to a BMI
- Lossless Bit-plane Compression of Microarray Images Using 3D Context Models
- Mathematic definitions and Formulas Antonio Rafael C. Paiva
- REVISTA DO DETUA, VOL. 4, N 2, JANEIRO 2004 235 Architectures for Open Access Hotspots
- Fast Semi-Supervised Image Segmentation Using Novelty Selection www.sci.utah.edu
- Luke Hogrebe, Antonio Paiva, Elizabeth Jurrus, Cameron Christensen, Michael Bridge, J.R. Korenberg, and Tolga Tasdizen Scientific Computing and Imaging Institute, Brain Institute, Dept. of Electrical and Computer Engineering, School of Computing
- Image Parsing with a Three-State Series Neural Network Classifier www.sci.utah.edu
- FAST SEMI-SUPERVISED IMAGE SEGMENTATION BY NOVELTY SELECTION Antonio R. C. Paiva1
- Inner products for representation and learning in the spike train domain
- TRACE DRIVEN REGISTRATION OF NEURON CONFOCAL MICROSCOPY STACKS Luke Hogrebe1,2
- Multi-scale Series Contextual Model for Image Parsing Mojtaba Seyedhosseini
- Detection of Salient Image Points using Principal Subspace Manifold Structure
- A comparison of binless spike train measures Antonio R. C. Paiva, Il Park, and Jose C. Principe
- An Efficient Algorithm for Continuous-time Cross Correlogram of Spike Trains
- Accepted Manuscript Self-organizing maps with dynamic learning for signal reconstruction
- IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 53, NO. 3, MARCH 2006 563 [7] 3SPACE FASTRAK User's Manual, Polhemus Incorporated, Colchester,
- A FIXED POINT UPDATE FOR KERNEL WIDTH ADAPTATION IN INFORMATION THEORETIC CRITERIA
- Abstract for 5th International Workshop on Statistical Analysis of Neuronal Data, May 2022, 2010, Pittsburgh, PA Which measure should we use for unsupervised spike train learning?
- Peri-event Cross-Correlation over Time for Analysis of Interactions in Neuronal Firing
- Peri-event Cross-Correlation over Time for Analysis of
- REPRODUCING KERNEL HILBERT SPACES FOR SPIKE TRAIN ANALYSIS Antonio R. C. Paiva1
- Reproducing kernel Hilbert Spaces for Spike Train Analysis
- A Novel Weighted LBG Algorithm for Neural Spike Compression Sudhir Rao, Antonio R. C. Paiva, Jose C. Principe
- Gravity Transform for Input Conditioning in
- Nonlinear Component Analysis Based on Correntropy Jian-Wu Xu, Puskal P. Pokharel, Antonio R. C. Paiva and Jose C. Principe
- Introduction CORRENTROPY PCA Results Nonlinear Component Analysis Based on
- Introduction Understanding Kernel PCA projections in input space Conclusions Kernel Principal Components are maximum
- Compression of Spike Data Using the Self-Organizing Map
- March 2005 1 Compression of Spike
- Demonstration of LATEX Beamer themes 1 Demonstration of LATEX Beamer themes
- [1] Abhishek Singh and Jose C. Principe, "Information theoretic learning with adaptive kernels," Signal Processing, 2010, [2] Abhishek Singh and Jose C. Principe, "Kernel width adaptation in information theoretic cost functions," in Proc. IEEE
- AUTOMATIC MARKUP OF NEURAL CELL MEMBRANES USING BOOSTED DECISION Kannan Umadevi Venkataraju1,2
- [1] J.-M. Fellous, P. H. E. Tiesinga, P. J. Thomas, and T. J. Sejnowski Discovering Spike Patterns in Neuronal Responses J. of Neuroscience, 24(12):2989-3001, March 2004.
- Gravity Transform for Input Conditioning in Brain Machine Interfaces Antonio R. C. Paiva, Jose C. Principe and Justin C. Sanchez
- Spectral Clustering of Synchronous Spike Trains Antonio R. C. Paiva, Sudhir Rao, Il Park and Jose C. Principe
- IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 56, NO. 12, DECEMBER 2008 5891 A Reproducing Kernel Hilbert Space Framework for
- An Efficient Computation of Continuous-time Correlogram of Spike Trains
- INTRODUCTION WNS-AdaBoost takes the outputs of the WNS to train the AdaBoost classifier.
