Nicholas A. Allgaier

Publication Activity (10 Years)

Years Active: 2013-2021
Publications (10 Years): 2

Top Topics

Machine Learning

Symbolic Regression

Disease Progression

Top Venues

Publications

Sage Hahn, Dekang Yuan, Wesley K. Thompson, Max M. Owens, Nicholas A. Allgaier, Hugh Garavan
Brain Predictability toolbox: a Python library for neuroimaging-based machine learning. Bioinform. 37 (11) (2021)
Sage Hahn, Dekang Yuan, Wesley K. Thompson, Max M. Owens, Nicholas A. Allgaier, Hugh Garavan
Brain Predictability toolbox: a Python library for neuroimaging based machine learning. CoRR (2020)
Nicholas A. Allgaier, Tobias Banaschewski, Gareth J. Barker, Arun L. W. Bokde, Josh C. Bongard, Uli Bromberg, Christian Büchel, Anna Cattrell, Patricia J. Conrod, Christopher M. Danforth, Sylvane Desrivières, Peter Sheridan Dodds, Herta Flor, Vincent Frouin, Jürgen Gallinat, Penny A. Gowland, Andreas Heinz, Bernd Ittermann, Scott Mackey, Jean-Luc Martinot, Kevin Murphy, Frauke Nees, Dimitri Papadopoulos-Orfanos, Luise Poustka, Michael N. Smolka, Henrik Walter, Robert A. Whelan, Gunter Schümann, Hugh Garavan
Nonlinear functional mapping of the human brain. CoRR (2015)
Ilknur Icke, Nicholas A. Allgaier, Christopher M. Danforth, Robert A. Whelan, Hugh P. Garavan, Joshua Clifford Bongard
A Deterministic and Symbolic Regression Hybrid Applied to Resting-State fMRI Data. GPTP (2013)