filmov
tv
Lecture 6: Gauge-equivariant Mesh CNN - Pim de Haan
Показать описание
Video recording of the First Italian School on Geometric Deep Learning held in Pescara in July 2022.
Lecture 6: Gauge-equivariant Mesh CNN - Pim de Haan
0:12:53
CSC2547 Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
0:16:57
Real-time CNNs to understand shift-equivariance, shift-variance, linearity and non-linearity
1:03:52
AMMI Course 'Geometric Deep Learning' - Lecture 10 (Gauges) - Taco Cohen
0:06:55
toy equivariant neural network visualised
0:20:04
Scalars are Universal: Gauge-equivariant Machine Learning, Structured Like Classical Physics
0:54:59
A New Perspective on Building Efficient and Expressive 3D Equivariant Graph Neural Networks
0:09:59
RIMeshGNN: A Rotation-Invariant Graph Neural Network for Mesh Classification
0:31:40
Group Equivariant Deep Learning - Lecture 3.7: Gauge equivariant graph NNs
0:33:08
Group Equivariant Deep Learning - Lecture 3.2: Equivariant message passing as non-linear convolution
0:27:43
Yi Zhou: Fully Convolutional Mesh Autoencoder Using Spatially Efficient Varying Kernels
0:46:54
AMMI 2022 Course 'Geometric Deep Learning' - Lecture 10 (Gauges) - Taco Cohen
1:27:20
Lecture 5: Equivariant CNNs II (Riemannian manifolds) - Maurice Weiler
1:11:40
Learning Equivariant and Hybrid Message Passing on Graphs | Max Welling
0:01:07
Training A Convolutional Neural Network to Output a Blum MedialAxis Skeleton - An Overview
0:06:02
110 Zhang HengKai-Mesh R CNN++ for 3D Mesh Generation From Single to Multiple Views
0:16:08
Group Equivariant Deep Learning - Lecture 1.5: A Brief History of G-CNNs
0:52:04
Pattern Recognition Symposium PRS Winter 20/21 - Pim de Haan - Natural Graph Networks
1:22:33
Maurice Weiler - Equivariant and Coordinate Independent Convolutional Networks
1:08:41
Equivariant RL
1:00:36
Lessons from Physics for Deep Learning
1:31:51
Lecture 4: Equivariant CNNs I (Euclidean Spaces) - Maurice Weiler
1:06:52
AMMI Course 'Geometric Deep Learning' - Lecture 7 (Grids) - Joan Bruna
0:52:42
Petar Veličkovć - Geometric Deep Learning: Grids, Graphs, Groups, Geodesics and Gauges
Комментарии