Deep learning and Bayesian inference for medical imaging

Información del proyecto

DeeBMED

Identificador del acuerdo de subvención: 702666

DOI 10.3030/702666

Proyecto cerrado

Fecha de la firma de la CE 17 Febrero 2016

Fecha de inicio 1 Octubre 2016

Fecha de finalización 30 Septiembre 2018

Financiado con arreglo a

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coste total € 177 598,80

Aportación de la UE € 177 598,80

Coordinado por

UNIVERSITEIT VAN AMSTERDAM
Netherlands

Publicaciones

Conference proceedings (11)

VAE with a VampPrior

Autores: Jakub Tomczak, Max Welling
Publicado en: Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, Edición PMLR 84, 2018, Página(s) 1214-1223
Editor: Journal of Machine Learning Research

Improving variational auto-encoders using householder flow

Autores: Jakub M Tomczak, Max Welling
Publicado en: Bayesian Deep Learning Workshop @ NIPS 2016, 2016, Página(s) 8
Editor: Bayesian Deep Learning Workshop @ NIPS 2016

Improving Variational Auto-Encoders using convex combination linear Inverse Autoregressive Flow

Autores: Jakub M. Tomczak, M Welling
Publicado en: Benelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning, 2017, Página(s) 162-164
Editor: TU/e

A deep multiple instance model to predict prostate cancer metastasis from nuclear morphology

Autores: Nathan Ing, Jakub M Tomczak, Eric Miller, Isla P Garraway, Max Welling, Beatrice S Knudsen, Arkadiusz Gertych
Publicado en: Medical Imaging with Deep Learning, 2018
Editor: OpenReview

Deep Learning with Order-invariant Operator for Multi-instance Histopathology Classification

Autores: Jakub Tomczak, Maximilian Ilse and Max Welling
Publicado en: MEDICAL IMAGING MEETS NIPS 2017, 2017
Editor: arXiv

Sylvester Normalizing Flows for Variational Inference

Autores: Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
Publicado en: Uncertainty in Artificial Intelligence Proceedings of the Thirty-Fourth Conference (2018), 2018
Editor: UAI 2018

Attention-based Deep Multiple Instance Learning

Autores: Maximilian Ilse, Jakub Tomczak, Max Welling
Publicado en: Volume 80: International Conference on Machine Learning, 10-15 July 2018, Stockholmsmässan, Stockholm Sweden, Edición PMLR 80, 2018, Página(s) 2127-2136
Editor: PMLR

Hierarchical VampPrior Variational Fair Auto-Encoder

Autores: Philip Botros and Jakub Tomczak
Publicado en: Theoretical Foundations and Applications of Deep Generative Models @ ICML 2018, 2018
Editor: Theoretical Foundations and Applications of Deep Generative Models @ ICML 2018

Variational Inference with Orthogonal Normalizing Flows

Autores: Leonard Hasenclever, Jakub Tomczak, Rianne van den Berg and Max Welling
Publicado en: Bayesian Deep Learning @ NIPS 2017, 2017
Editor: Bayesian Deep Learning @ NIPS 2017

Histopathological classification of precursor lesions of esophageal adenocarcinoma: A Deep Multiple Instance Learning Approach

Autores: Jakub M Tomczak, Maximilian Ilse, Max Welling, Marnix Jansen, Helen G Coleman, Marit Lucas, Kikki de Laat, Martijn de Bruin, Henk Marquering, Myrtle J van der Wel, Onno J de Boer, C Dilara Savci Heijink, Sybren L Meijer
Publicado en: Medical Imaging with Deep Learning, 2018
Editor: OpenReview

Hyperspherical Variational Auto-Encoders

Autores: Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, Jakub M. Tomczak
Publicado en: Uncertainty in Artificial Intelligence Proceedings of the Thirty-Fourth Conference (2018), 2018
Editor: UAI 2018