4 citations · 4 across the 2 of their papers we have counts for
3 papers
OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens
Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert +18
Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains un…
Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction
Muhammad U. Mirza, Onat Dalmaz, Hasan A. Bedel +5
Deep generative models have gained recent traction in accelerated MRI reconstruction. Diffusion priors are particularly promising given their representational fidelity. Instead of…
DreaMR: Diffusion-driven Counterfactual Explanation for Functional MRI
Hasan Atakan Bedel, Tolga Çukur
Deep learning analyses have offered sensitivity leaps in detection of cognitive states from functional MRI (fMRI) measurements across the brain. Yet, as deep models perform hierarc…