1 citations · 1 across the 5 of their papers we have counts for
6 papers · 1 filter
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach
Alexander Lin, Yingzhuo Zhang, Jeremy Heng +4
We propose a general statistical framework for clustering multiple time series that exhibit nonlinear dynamics into an a-priori-unknown number of sub-groups. Our motivation comes f…
Sequential Detection of Regime Changes in Neural Data
Taposh Banerjee, Stephen Allsop, Kay M. Tye +2
The problem of detecting changes in firing patterns in neural data is studied. The problem is formulated as a quickest change detection problem. Important algorithms from the liter…
Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-encoders
Bahareh Tolooshams, Sourav Dey, Demba Ba
Given a convolutional dictionary underlying a set of observed signals, can a carefully designed auto-encoder recover the dictionary in the presence of noise? We introduce an auto-e…
Deeply-Sparse Signal rePresentations ()
Demba Ba
A recent line of work shows that a deep neural network with ReLU nonlinearities arises from a finite sequence of cascaded sparse coding models, the outputs of which, except for the…
Spike Sorting by Convolutional Dictionary Learning
Andrew H. Song, Francisco Flores, Demba Ba
Spike sorting refers to the problem of assigning action potentials observed in extra-cellular recordings of neural activity to the neuron(s) from which they originate. We cast this…
Multitaper Spectral Estimation HDP-HMMs for EEG Sleep Inference
Leon Chlon, Andrew Song, Sandya Subramanian +4
Electroencephalographic (EEG) monitoring of neural activity is widely used for sleep disorder diagnostics and research. The standard of care is to manually classify 30-second epoch…