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Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems and optimal experimental design
Presenter
- Omar Ghattas
October 7, 2020
IMSI
Learning Over-parameterized Neural Networks: From Neural Tangent Kernel to Mean-field Analysis
Presenter
- Quanquan Gu
April 23, 2020
IPAM
New deep neural networks solving non-linear inverse problems
Presenter
- Matti Lassas
April 20, 2020
IPAM
Tutorial - Introductory Talk - Data-Driven Reduced Order Models As Deep Prior Neural Networks In Inverse Scattering
Presenter
- Mikhail Zaslavsky
February 7, 2020
ICERM
On Bayesian models with networks for reconstruction and detection
Presenter
- Ender Konukoglu
January 30, 2020
IPAM
Machine learning with neural networks: the importance of data structure
Presenter
- Marc Mezard
November 21, 2019
IPAM
On the Connection between Neural Networks and Kernels: a Modern Perspective
Presenter
- Simon Du
October 16, 2019
IAS
Dynamics of Deep Neural Networks--A Fourier Analysis Perspective
Presenter
- Yaoyu Zhang
October 4, 2019
IAS