research
∙
01/11/2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Self-supervised learning in vision-language processing exploits semantic...
share
research
∙
03/08/2021
Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions
Unobserved confounding is one of the main challenges when estimating cau...
research
∙
11/03/2020
Problems using deep generative models for probabilistic audio source separation
Recent advancements in deep generative modeling make it possible to lear...
research
∙
05/04/2020
Designing Data Augmentation for Simulating Interventions
Machine learning models trained with purely observational data and the p...
research
∙
05/24/2019
DIVA: Domain Invariant Variational Autoencoders
We consider the problem of domain generalization, namely, how to learn r...
research
∙
02/13/2018
Attention-based Deep Multiple Instance Learning
Multiple instance learning (MIL) is a variation of supervised learning w...
research
∙
12/01/2017
