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Fully Hyperbolic Convolutional Neural Networks

Fully Hyperbolic Convolutional Neural Networks

24 May 2019
Keegan Lensink
Bas Peters
E. Haber
    MedIm
ArXivPDFHTML

Papers citing "Fully Hyperbolic Convolutional Neural Networks"

8 / 8 papers shown
Title
Good Things Come in Pairs: Paired Autoencoders for Inverse Problems
Good Things Come in Pairs: Paired Autoencoders for Inverse Problems
Matthias Chung
Bas Peters
Michael Solomon
39
0
0
10 May 2025
InvertibleNetworks.jl: A Julia package for scalable normalizing flows
InvertibleNetworks.jl: A Julia package for scalable normalizing flows
Rafael Orozco
Philipp A. Witte
M. Louboutin
Ali Siahkoohi
G. Rizzuti
Bas Peters
Felix J. Herrmann
38
9
0
20 Dec 2023
Hyperbolic Convolution via Kernel Point Aggregation
Hyperbolic Convolution via Kernel Point Aggregation
Eric Qu
Dongmian Zou
55
3
0
15 Jun 2023
Estimating a potential without the agony of the partition function
Estimating a potential without the agony of the partition function
E. Haber
Moshe Eliasof
L. Tenorio
33
2
0
19 Aug 2022
Learning by example: fast reliability-aware seismic imaging with
  normalizing flows
Learning by example: fast reliability-aware seismic imaging with normalizing flows
Ali Siahkoohi
Felix J. Herrmann
OOD
29
13
0
13 Apr 2021
Point-to-set distance functions for weakly supervised segmentation
Point-to-set distance functions for weakly supervised segmentation
Bas Peters
18
1
0
27 Jul 2020
Parameterizing uncertainty by deep invertible networks, an application
  to reservoir characterization
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization
G. Rizzuti
Ali Siahkoohi
Philipp A. Witte
Felix J. Herrmann
UQCV
33
20
0
16 Apr 2020
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
306
10,378
0
12 Dec 2018
1