Matthew Lawlor and Steven W. Zucker: Tensor decomposition by modified BCM neurons
finds mixture means through input triplets.[Paper]
Mayur Mudigonda, Nicolas Muller, Aditya Joshi, Christopher Hillar, and Friedrich Sommer:
Learning non-local features for classification
using compressed sensing and sparse coding
Michael D. Oliver and Dustin E. Stansbury:
Learning non-linear receptive field models of V2 neurons using deep networks
Jacquelyn A. Shelton, Abdul-Saboor Sheikh, Philip Sterne, Jorg Bornschein and Jorg Lucke
Nonlinear spike-and-slab sparse coding for
interpretable image encoding
High-Dimensional Statistical Inference in the Brain
Schedule
Posters-
S. Zayd Enam and Michael R. DeWeese:
Time-frequency inseparable receptive field models.
[Paper]
-
T. Furlanello, M. Cristoforetti, C. Furlanello and G. Jurman:
Sparse predictive structure of deconvolved functional brain networks
[Poster]
[Paper]
-
Matthew Lawlor and Steven W. Zucker: Tensor decomposition by modified BCM neurons
finds mixture means through input triplets.
[Paper]
-
Mayur Mudigonda, Nicolas Muller, Aditya Joshi, Christopher Hillar, and Friedrich Sommer:
Learning non-local features for classification
using compressed sensing and sparse coding
-
Michael D. Oliver and Dustin E. Stansbury:
Learning non-linear receptive field models of V2 neurons using deep networks
-
Jacquelyn A. Shelton, Abdul-Saboor Sheikh, Philip Sterne, Jorg Bornschein and Jorg Lucke
Nonlinear spike-and-slab sparse coding for
interpretable image encoding
-
Mengchen Zhu, Ian Stevenson, Urs Köster, Charles M. Gray,
Bruno A. Olshausen, and Christopher Rozell:
Modeling single-trial V1 population response to
dynamic natural scenes