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1805.11178
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Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
28 May 2018
Alexander Binder
M. Bockmayr
Miriam Hagele
S. Wienert
Daniel Heim
Katharina Hellweg
A. Stenzinger
Laura Parlow
J. Budczies
B. Goeppert
D. Treue
Manato Kotani
M. Ishii
M. Dietel
A. Hocke
C. Denkert
K. Müller
Frederick Klauschen
AI4CE
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Papers citing
"Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles"
6 / 6 papers shown
Title
Quantifying Explainers of Graph Neural Networks in Computational Pathology
Guillaume Jaume
Pushpak Pati
Behzad Bozorgtabar
Antonio Foncubierta-Rodríguez
Florinda Feroce
A. Anniciello
T. Rau
Jean-Philippe Thiran
M. Gabrani
O. Goksel
FAtt
26
76
0
25 Nov 2020
It's All in the Name: A Character Based Approach To Infer Religion
Rochana Chaturvedi
Sugat Chaturvedi
24
23
0
27 Oct 2020
How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks
Kirill Bykov
Marina M.-C. Höhne
Klaus-Robert Muller
Shinichi Nakajima
Marius Kloft
UQCV
FAtt
27
31
0
16 Jun 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
Wojciech Samek
G. Montavon
Sebastian Lapuschkin
Christopher J. Anders
K. Müller
XAI
51
82
0
17 Mar 2020
Towards Explainable Artificial Intelligence
Wojciech Samek
K. Müller
XAI
32
436
0
26 Sep 2019
Software and application patterns for explanation methods
Maximilian Alber
38
11
0
09 Apr 2019
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