TA1a.3

Learning Efficient Implicit Neural Representations for Low Data Settings with Structured Noise

Kushal Vyas, Ashok Veeraraghavan, Guha Balakrishnan, Rice University, United States
Session:
TA1a: Theory and Applications of Implicit Neural Representations for Inverse Problems Lecture
Track:
Speech, Image and Video Processing
Location:
Heather
Presentation Time:
Tue, 28 Oct, 09:05 - 09:30 PT (UTC -8)
Session Co-Chairs:
Vishwanath Saragadam, University of California, Riverside and Vivek Boominathan, Rice University
Presentation
Discussion
Resources
No resources available.
Session TA1a
TA1a.1: NEWER: Neural Estimation of Wavelet-Embedded Representations
Vishesh Kumar, Rice University, United States; Vishwanath Saragadam, UC Riverside, United States; Vivek Boominathan, Rice University, United States
TA1a.2: Implicit and Explicit Volumetric Representations for Sensor Fusion
Zihao Zou, University of North Carolina at Chapel Hill, United States; Ziyuan Qu, Dartmouth College, United States; Suren Jayasuriya, Arizona State University, United States; Adithya Pediredla, Dartmouth College, United States; Praneeth Chakravarthula, University of North Carolina at Chapel Hill, United States
TA1a.3: Learning Efficient Implicit Neural Representations for Low Data Settings with Structured Noise
Kushal Vyas, Ashok Veeraraghavan, Guha Balakrishnan, Rice University, United States
TA1a.4: Extended Field of View mmWave Imaging with Implicit Neural Representations
Sanjaya Herath, University of Maryland, United States; Matthew Ziemann, DEVCOM Army Research Laboratory, United States; Christopher Metzler, University of Maryland, United States
Contacts