120 citations · 871 across the 41 of their papers we have counts for
6 papers · 1 filter
Grand Challenges for Global Brain Sciences
Joshua T. Vogelstein, Katrin Amunts, Andreas Andreou +59
The next grand challenges for society and science are in the brain sciences. A collection of 60+ scientists from around the world, together with 10+ observers from national, privat…
Towards an integration of deep learning and neuroscience
Adam Marblestone, Greg Wayne, Konrad Kording
Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend…
Science Concierge: A fast content-based recommendation system for scientific publications
Titipat Achakulvisut, Daniel E. Acuna, Tulakan Ruangrong +1
Finding relevant publications is important for scientists who have to cope with exponentially increasing numbers of scholarly material. Algorithms can help with this task as they h…
Quantifying mesoscale neuroanatomy using X-ray microtomography
Eva L. Dyer, William Gray Roncal, Hugo L. Fernandes +9
Methods for resolving the 3D microstructure of the brain typically start by thinly slicing and staining the brain, and then imaging each individual section with visible light photo…
From sample to knowledge: Towards an integrated approach for neuroscience discovery
William Gray Roncal, Eva L Dyer, Doga Gürsoy +2
Imaging methods used in modern neuroscience experiments are quickly producing large amounts of data capable of providing increasing amounts of knowledge about neuroanatomy and func…
Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes
Mohammad Gheshlaghi Azar, Eva Dyer, Konrad Kording
Finding efficient and provable methods to solve non-convex optimization problems is an outstanding challenge in machine learning and optimization theory. A popular approach used to…