2 citations · 3 across the 4 of their papers we have counts for
4 papers
Multi-task learning on partially labeled datasets via invariant/equivariant semi-supervised learning
Miquel Martí i Rabadán, Alessandro Pieropan, Hossein Azizpour +1
We investigate the potential of invariant and equivariant semi-supervised learning for addressing the challenges of training multi-task models on partially labeled datasets with di…
Deep Probabilistic Supervision for Image Classification
Anton Adelöw, Matteo Gamba, Atsuto Maki
Supervised training of deep neural networks for classification typically relies on hard targets, which promote overconfidence and can limit calibration, generalization, and robustn…
NT-ViT: Neural Transcoding Vision Transformers for EEG-to-fMRI Synthesis
Romeo Lanzino, Federico Fontana, Luigi Cinque +2
This paper introduces the Neural Transcoding Vision Transformer (\modelname), a generative model designed to estimate high-resolution functional Magnetic Resonance Imaging (fMRI) s…
ZoDi: Zero-Shot Domain Adaptation with Diffusion-Based Image Transfer
Hiroki Azuma, Yusuke Matsui, Atsuto Maki
Deep learning models achieve high accuracy in segmentation tasks among others, yet domain shift often degrades the models' performance, which can be critical in real-world scenario…