
Manifold Learning and Deep Clustering with Local Dictionaries
We introduce a novel clustering algorithm for data sampled from a union ...
read it

PLSO: A generative framework for decomposing nonstationary timeseries into piecewise stationary oscillatory components
To capture the slowly timevarying spectral content of realworld time s...
read it

Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution
We propose a learnedstructured unfolding neural network for the problem...
read it

Dense and Sparse Coding: Theory and Architectures
The sparse representation model has been successfully utilized in a numb...
read it

RandNet: deep learning with compressed measurements of images
Principal component analysis, dictionary learning, and autoencoders are...
read it

Convolutional Dictionary Learning in Hierarchical Networks
Filter banks are a popular tool for the analysis of piecewise smooth sig...
read it

Fast Convolutional Dictionary Learning off the Grid
Given a continuoustime signal that can be modeled as the superposition ...
read it

Deep ExponentialFamily AutoEncoders
We consider the problem of learning recurring convolutional patterns fro...
read it

Deep Residual AutoEncoders for Expectation Maximizationbased Dictionary Learning
Convolutional dictionary learning (CDL) has become a popular method for ...
read it

Clustering Time Series with Nonlinear Dynamics: A Bayesian NonParametric and ParticleBased Approach
We propose a statistical framework for clustering multiple time series t...
read it

Sequential Detection of Regime Changes in Neural Data
The problem of detecting changes in firing patterns in neural data is st...
read it

Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Autoencoders
Given a convolutional dictionary underlying a set of observed signals, c...
read it

DeeplySparse Signal rePresentations (DS^2P)
The solution to the regularized leastsquares problem min_x∈R^p+1/2yAx_...
read it

Spike Sorting by Convolutional Dictionary Learning
Spike sorting refers to the problem of assigning action potentials obser...
read it

Multitaper Spectral Estimation HDPHMMs for EEG Sleep Inference
Electroencephalographic (EEG) monitoring of neural activity is widely us...
read it

Wavelet Shrinkage and Thresholding based Robust Classification for Brain Computer Interface
A macaque monkey is trained to perform two different kinds of tasks, mem...
read it

Estimating a SeparablyMarkov Random Field (SMuRF) from Binary Observations
A fundamental problem in neuroscience is to characterize the dynamics of...
read it

A Modularized Efficient Framework for NonMarkov Time Series Estimation
We present a compartmentalized approach to finding the maximum aposteri...
read it
Demba Ba
is this you? claim profile