Maximilian Ilse

According to our database, Maximilian Ilse authored at least 12 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision.

Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Matthew P. Lungren, Maria Wetscherek, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, Ozan Oktay

CoRR, 2024

2023

RadEdit: stress-testing biomedical vision models via diffusion image editing.

Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel C. Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse

CoRR, 2023

AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires.

Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds

Proceedings of the Machine Learning for Healthcare Conference, 2023

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing.

Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021

Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions.

Maximilian Ilse, Patrick Forré, Max Welling, Joris M. Mooij

CoRR, 2021

Selecting Data Augmentation for Simulating Interventions.

Maximilian Ilse, Jakub M. Tomczak, Patrick Forré

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Designing Data Augmentation for Simulating Interventions.

Maximilian Ilse, Jakub M. Tomczak, Patrick Forré

CoRR, 2020

DIVA: Domain Invariant Variational Autoencoders.

Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Problems using deep generative models for probabilistic audio source separation.

Maurice Frank, Maximilian Ilse

Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

2019

DIVA: Domain Invariant Variational Autoencoder.

Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Attention-based Deep Multiple Instance Learning.

Maximilian Ilse, Jakub M. Tomczak, Max Welling

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification.

Jakub M. Tomczak, Maximilian Ilse, Max Welling

CoRR, 2017