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Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis
16 July 2024
Cécile Trottet
Manuel Schürch
Ahmed Allam
Imon Barua
L. Petelytska
David Launay
Paolo Airò
Radim Bečvář
Christopher Denton
Mislav Radic
Oliver Distler
A. Hoffmann-Vold
Michael Krauthammer
Eustar collaborators
MedIm
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Papers citing
"Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis"
17 / 17 papers shown
Title
Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression
Shahriar Noroozizadeh
Jeremy C. Weiss
George H. Chen
119
8
0
10 Dec 2023
Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration
R. Holland
Oliver Leingang
Christopher Holmes
Philipp Anders
Rebecca Kaye
...
H. Scholl
S. Sivaprasad
A. Lotery
Daniel Rueckert
Martin J. Menten
46
2
0
11 Jan 2023
SW-VAE: Weakly Supervised Learn Disentangled Representation Via Latent Factor Swapping
Jiageng Zhu
Hanchen Xie
Wael AbdAlmageed
SSL
CoGe
DRL
57
4
0
21 Sep 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case
Clément Chadebec
Louis J. Vincent
S. Allassonnière
DRL
89
30
0
16 Jun 2022
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation
Francesco Locatello
Stefan Bauer
Mario Lucic
Gunnar Rätsch
Sylvain Gelly
Bernhard Schölkopf
Olivier Bachem
OOD
75
70
0
27 Oct 2020
Probabilistic Machine Learning for Healthcare
Irene Y. Chen
Shalmali Joshi
Marzyeh Ghassemi
Rajesh Ranganath
OOD
61
56
0
23 Sep 2020
Longitudinal Variational Autoencoder
S. Ramchandran
Gleb Tikhonov
Kalle Kujanpää
Miika Koskinen
Harri Lähdesmäki
DRL
CML
BDL
78
37
0
17 Jun 2020
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGe
OOD
DRL
244
320
0
07 Feb 2020
MGP-AttTCN: An Interpretable Machine Learning Model for the Prediction of Sepsis
Margherita Rosnati
Vincent Fortuin
94
34
0
27 Sep 2019
Recursive Estimation for Sparse Gaussian Process Regression
Manuel Schürch
Dario Azzimonti
A. Benavoli
Marco Zaffalon
63
33
0
28 May 2019
Gaussian Process Prior Variational Autoencoders
F. P. Casale
Adrian Dalca
Luca Saglietti
Jennifer Listgarten
Nicolò Fusi
BDL
CML
71
138
0
28 Oct 2018
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGe
OOD
70
1,356
0
16 Feb 2018
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDL
SSL
OCL
238
5,079
0
02 Nov 2017
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
Wei-Ning Hsu
Yu Zhang
James R. Glass
BDL
SSL
84
354
0
22 Sep 2017
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
307
4,812
0
04 Jan 2016
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
458
16,922
0
20 Dec 2013
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
286
12,460
0
24 Jun 2012
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