WA8b1: Deep Learning |
Session Type: Poster |
Time: Wednesday, November 6, 10:15 - 11:30 |
Location: Merrill |
Session Chair: Maxime Guillaud, Huawei |
WA8b1-1: COUNTING LATTICE POINTS IN THE SPHERE USING DEEP NEURAL NETWORKS |
Aymen Askri; Télécom ParisTech |
Ghaya Rekaya-Ben Othman; Télécom ParisTech |
Hadi Ghauch; Télécom ParisTech |
WA8b1-2: DSP-INSPIRED DEEP LEARNING: A CASE STUDY USING RAMANUJAN SUBSPACES |
Srikanth Tenneti; Amazon Web Services |
P. P. Vaidyanathan; California Institute of Technology |
WA8b1-3: MEDA: MULTI-OUTPUT ENCODER-DECODER FOR SPATIAL ATTENTION IN CONVOLUTIONAL NEURAL NETWORKS |
Huayu Li; Northern Arizona University |
Abolfazl Razi; Northern Arizona University |
WA8b1-4: LOSS FUNCTIONS FORCING CLUSTER SEPARATIONS FOR MULTI-CLASS CLASSIFICATION USING DEEP NEURAL NETWORKS |
Li Li; George Washington University |
Milos Doroslovacki; George Washington University |
Murray Loew; George Washington University |
WA8b1-5: LEARNING STRUCTURED SIGNALS USING GANS WITH APPLICATIONS IN DENOISING AND DEMIXING |
Mohammadreza Soltani; Iowa State university |
Swayambhoo Jain; Technicolor AI Labs |
Abhinav V. Sambasivan; University of Minnesota |
Chinmay Hegde; Iowa State University |
WA8b1-7: WAVE EQUATION EXTRACTION FROM A VIDEO USING SPARSE MODELING |
Ruixian Liu; University of California, San Diego |
Michael Bianco; University of California, San Diego |
Peter Gerstoft; University of California, San Diego |
WA8b1-8: THE AUTOENCODER-KALMAN FILTER: THEORY AND PRACTICE |
Matthew Weiss; Worcester Polytechnic Institute |
Joshua Uzarski; U.S. Army Combat Capabilities Development Command Soldier Center |
Randy Paffenroth; Worcester Polytechnic Institute |