4 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
Samples, Sources, Space: Decomposing Data Scale in Spatially Structured Representation Learning of Human Brain Microarchitecture
Christian Schiffer, Mathis Bode, Thomas Lippert +2
Scaling studies typically represent training data by a single count of samples. For hierarchically and spatially structured data, however, the same number of samples can be drawn f…
Quantum Deep Learning: A Comprehensive Review
Yanjun Ji, Zhao-Yun Chen, Marco Roth +10
Quantum deep learning (QDL) explores the use of both quantum and quantum-inspired resources to determine when deep learning's core capabilities, such as expressivity, generalizatio…
Cytoarchitecture in Words: Weakly Supervised Vision-Language Modeling for Human Brain Microscopy
Matthew Sutton, Katrin Amunts, Timo Dickscheid +1
Vision foundation models increasingly support interactive scientific workflows, but natural-language interaction requires coupling visual representations to language. Curated image…