Tanya Schmah

Filtered noise can mimic low-dimensional chaotic attractors

Paul E. Rapp, A. M. Albano, Tanya Schmah et al. · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · 1993 · 243 citations

Attractor, Engineering, Chaos Theory +12

Generative versus discriminative training of RBMs for classification of fMRI images

Tanya Schmah, Geoffrey E. Hinton, Steven L. Small et al. · 2008 · 65 citations

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data

Anthony L. Vaccarino, Moyez Dharsee, Stephen C. Strother et al. · Frontiers in Neuroinformatics · 2018 · 64 citations · Full text

Secure Neuroinformatics Platform, Engineering, Databases +24

Comparing Classification Methods for Longitudinal fMRI Studies

Tanya Schmah, Grigori Yourganov, Richard S. Zemel et al. · Neural Computation · 2010 · 42 citations

Engineering, Machine Learning, Support Vector Machine +22

SURROGATE DATA PATHOLOGIES AND THE FALSE-POSITIVE REJECTION OF THE NULL HYPOTHESIS

Paul E. Rapp, Christopher J. Cellucci, Tomas Watanabe et al. · International Journal of Bifurcation and Chaos · 2001 · 37 citations

The Null Hypothesis, Engineering, Statistical Foundation +17