55 citations · 78 across the 4 of their papers we have counts for
10 papers
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes
Alex Fedorov, Eloy Geenjaar, Lei Wu +7
Recent neuroimaging studies that focus on predicting brain disorders via modern machine learning approaches commonly include a single modality and rely on supervised over-parameter…
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease
Alex Fedorov, Tristan Sylvain, Eloy Geenjaar +7
Sensory input from multiple sources is crucial for robust and coherent human perception. Different sources contribute complementary explanatory factors. Similarly, research studies…
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations
Tristan Sylvain, Linda Petrini, R Devon Hjelm
Zero-shot classification is a generalization task where no instance from the target classes is seen during training. To allow for test-time transfer, each class is annotated with s…
Cross-Modal Information Maximization for Medical Imaging: CMIM
Tristan Sylvain, Francis Dutil, Tess Berthier +4
In hospitals, data are siloed to specific information systems that make the same information available under different modalities such as the different medical imaging exams the pa…
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
Matthew Amodio, Rim Assouel, Victor Schmidt +3
Unsupervised image-to-image translation consists of learning a pair of mappings between two domains without known pairwise correspondences between points. The current convention is…
Object-Centric Image Generation from Layouts
Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio +2
Despite recent impressive results on single-object and single-domain image generation, the generation of complex scenes with multiple objects remains challenging. In this paper, we…