TP5a: Deep Learning and Neuroscience (Invited) |
| Session Type: Oral |
| Time: Tuesday, November 5, 13:30 - 15:10 |
| Location: Scripps |
| Session Chair: Eva Dyer, Georgia Tech |
| TP5a-1: MODELING VARIABILITY IN BRAIN ARCHITECTURE WITH DEEP FEATURE LEARNING |
| Aishwarya Balwani; Georgia Institute of Technology |
| Eva Dyer; Georgia Institute of Technology |
| TP5a-2: REVERSE ENGINEERING NEURAL NETWORKS TO UNDERSTAND HOW TO REVERSE ENGINEER BRAINS |
| Konrad Kording; University of Pennsylvania |
| David Rolnick; UPenn |
| TP5a-3: SYNTHETIC POWER ANALYSES: EMPIRICAL EVALUATION AND APPLICATION TO COGNITIVE NEUROIMAGING |
| Peiye Zhuang; University of Illinois at Urbana-Champaign |
| Bliss Chapman; University of Illinois at Urbana-Champaign |
| Ran Li; University of Illinois at Urbana-Champaign |
| Sanmi Koyejo; University of Illinois at Urbana-Champaign |
| TP5a-4: TRANSFER LEARNING ANALYSIS OF IMAGE PROCESSING WORKFLOWS FOR ELECTRON MICROSCOPY DATASETS |
| Erik Johnson; Johns Hopkins University Applied Physics Laboratory |
| Luis Rodriguez; Johns Hopkins University Applied Physics Laboratory |
| Raphael Norman-Tenazas; Johns Hopkins University Applied Physics Laboratory |
| Daniel Xenes; Johns Hopkins University Applied Physics Laboratory |
| William Gray-Roncal; Johns Hopkins University Applied Physics Laboratory |