no code implementations • 24 Jun 2022 • James Macglashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone
These value estimates provide insight into an agent's learning and decision-making process and enable new training methods to mitigate common problems.
no code implementations • NeurIPS 2017 • Artur Speiser, Jinyao Yan, Evan Archer, Lars Buesing, Srinivas C. Turaga, Jakob H. Macke
Calcium imaging permits optical measurement of neural activity.
no code implementations • NeurIPS 2016 • Yuanjun Gao, Evan Archer, Liam Paninski, John P. Cunningham
A body of recent work in modeling neural activity focuses on recovering low-dimensional latent features that capture the statistical structure of large-scale neural populations.
no code implementations • 23 Nov 2015 • Evan Archer, Il Memming Park, Lars Buesing, John Cunningham, Liam Paninski
These models have the advantage of learning latent structure both from noisy observations and from the temporal ordering in the data, where it is assumed that meaningful correlation structure exists across time.
2 code implementations • 2 Feb 2013 • Evan Archer, Il Memming Park, Jonathan Pillow
The Pitman-Yor process, a generalization of Dirichlet process, provides a tractable prior distribution over the space of countably infinite discrete distributions, and has found major applications in Bayesian non-parametric statistics and machine learning.
Information Theory Information Theory
no code implementations • NeurIPS 2012 • Evan Archer, Il Memming Park, Jonathan W. Pillow
We consider the problem of estimating Shannon's entropy H in the under-sampled regime, where the number of possible symbols may be unknown or countably infinite.