Tootfinder

Beyond Grid-Locked Voxels: Neural Response Functions for Continuous Brain Encoding
Haomiao Chen, Keith W Jamison, Mert R. Sabuncu, Amy Kuceyeski
https://arxiv.org/abs/2510.07342

Beyond Grid-Locked Voxels: Neural Response Functions for Continuous Brain Encoding
Neural encoding models aim to predict fMRI-measured brain responses to natural images. fMRI data is acquired as a 3D volume of voxels, where each voxel has a defined spatial location in the brain. However, conventional encoding models often flatten this volume into a 1D vector and treat voxel responses as independent outputs. This removes spatial context, discards anatomical information, and ties each model to a subject-specific voxel grid. We introduce the Neural Response Function (NRF), a fra…

Resource-efficient universal photonic processor based on time-multiplexed hybrid architectures
Jonas Lammers, Laura Ares, Federico Pegoraro, Philip Held, Benjamin Brecht, Jan Sperling, Christine Silberhorn
https://arxiv.org/abs/2509.22521

Resource-efficient universal photonic processor based on time-multiplexed hybrid architectures
For the ever-growing field of quantum information processing, large-scale, efficient multi-port interferometers serving as photonic processors are required. In this context, the suitability of quantum walks as the interferometric base for universal computation has been theoretically proven. In this work, we bridge the gap between theoretical proposals and state-of-the-art experimental capabilities by providing the recipe for the implementation of a universal photonic processor in discrete-time …