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CONVOLUTIONAL NEURAL NETWORKS
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Classroom Contents
Inverse Problems on Graphs with Geometric Deep Learning
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- 1 Intro
- 2 DEEP LEARNING ON REGULAR GRIDS
- 3 TOWARDS NON-EUCLIDEAN GEOMETRIES
- 4 PHYSICS-BASED GEOMETRIC LEARNING
- 5 GEOMETRIC STABILITY IN EUCLIDEAN DOMAINS
- 6 CONVOLUTIONAL NEURAL NETWORKS
- 7 NON-EUCLIDEAN GEOMETRIC STABILITY
- 8 DEFORMATIONS AND METRICS
- 9 DIFFUSION AND METRIC STABILITY
- 10 LINEAR STABLE GENERATORS
- 11 LAPLACIAN INTERPRETATION
- 12 SURFACE REPRESENTATIONS
- 13 PARTICLE PHYSICS WITH GRAPH NEURAL NETWORKS
- 14 ICECUBE NEUTRINO DETECTION
- 15 INVERSE PROBLEMS ON GRAPHS
- 16 DABL-DRIVEN COMMUNITY DETECTION
- 17 REACHING DETECTION THRESHOLD ON SEM
- 18 GRAPH NEURAL NETWORKS ON GRAPH HIERARCHES
- 19 COMPUTATIONAL-TO-STATISTICAL GAPS
- 20 SUPERVISED COMMUNITY DETECTION
- 21 CURRENT AND OPEN PROBLEMS
