17 citations · 27 across the 6 of their papers we have counts for
7 papers
Interpolating between sampling and variational inference with infinite stochastic mixtures
Richard D. Lange, Ari Benjamin, Ralf M. Haefner +1
Sampling and Variational Inference (VI) are two large families of methods for approximate inference that have complementary strengths. Sampling methods excel at approximating arbit…
Object Based Attention Through Internal Gating
Jordan Lei, Ari S. Benjamin, Konrad P. Kording
Object-based attention is a key component of the visual system, relevant for perception, learning, and memory. Neurons tuned to features of attended objects tend to be more active…
Augmenting Supervised Learning by Meta-learning Unsupervised Local Rules
Jeffrey Cheng, Ari Benjamin, Benjamin Lansdell +1
The brain performs unsupervised learning and (perhaps) simultaneous supervised learning. This raises the question as to whether a hybrid of supervised and unsupervised methods will…
Learning to infer in recurrent biological networks
Ari S. Benjamin, Konrad P. Kording
A popular theory of perceptual processing holds that the brain learns both a generative model of the world and a paired recognition model using variational Bayesian inference. Most…
Measuring and regularizing networks in function space
Ari S. Benjamin, David Rolnick, Konrad Kording
To optimize a neural network one often thinks of optimizing its parameters, but it is ultimately a matter of optimizing the function that maps inputs to outputs. Since a change in…
The Roles of Supervised Machine Learning in Systems Neuroscience
Joshua I. Glaser, Ari S. Benjamin, Roozbeh Farhoodi +1
Over the last several years, the use of machine learning (ML) in neuroscience has been rapidly increasing. Here, we review ML's contributions, both realized and potential, across s…