919 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Massachusetts Institute of TechnologyUS27 papers
- Harvard UniversityUS7 papers
- Institute of Cognitive and Brain SciencesUS7 papers
- Chinese Institute for Brain ResearchCN5 papers
- Tsinghua UniversityCN4 papers
- Beijing Academy of Artificial IntelligenceCN3 papers
- Beijing Normal UniversityCN3 papers
- Columbia UniversityUS3 papers
- Harvard–MIT Division of Health Sciences and TechnologyUS3 papers
- IIT@MITUS3 papers
- Italian Institute of TechnologyIT3 papers
- University of California, BerkeleyUS3 papers
5 papers · 1 filter
Bio-realistic and versatile artificial dendrites made of anti-ambipolar transistors
Yifei Yang, Mingkun Xu, Jing Pei +4
The understanding of neural networks as neuron-synapse binaries has been the foundation of neuroscience, and therefore, the emerging neuromorphic computing technology that takes in…
Space-variant Shack-Hartmann wavefront sensing based on affine transformation estimation
Fan Feng, Chen Liang, Dongdong Chen +7
The space-variant wavefront reconstruction problem inherently exists in deep tissue imaging. In this paper,we propose a framework of Shack-Hartmann wavefront space-variant sensing…
Physical Computing: A Category Theoretic Perspective on Physical Computation and System Compositionality
Nima Dehghani, Gianluca Caterina
This paper introduces a category theory-based framework to redefine physical computing in light of advancements in quantum computing and non-standard computing systems. By integrat…
Beyond linear regression: mapping models in cognitive neuroscience should align with research goals
Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti +3
Many cognitive neuroscience studies use large feature sets to predict and interpret brain activity patterns. Feature sets take many forms, from human stimulus annotations to repres…
Interpretability of artificial neural network models in artificial Intelligence vs. neuroscience
Kohitij Kar, Simon Kornblith, Evelina Fedorenko
Computationally explicit hypotheses of brain function derived from machine learning (ML)-based models have recently revolutionized neuroscience. Despite the unprecedented ability o…