Keywords
Neural codingPerceptionBayes' theoremSensory systemBayesian probabilityNeurophysiologyComputer scienceBayesian inferenceCoding (social sciences)PsychophysicsArtificial intelligenceComputational neurosciencePsychologyModels of neural computationComputational modelMachine learningNeuroscienceArtificial neural networkMathematics
Affiliated Institutions
Related Publications
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Preface 1 Overview of Learning Systems 1.1 What is a Learning System? 1.2 Motivation for Building Learning Systems 1.3 Types of Practical Empirical Learning Systems 1.3.1 Common...
Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning
Deep learning tools have gained tremendous attention in applied machine\nlearning. However such tools for regression and classification do not capture\nmodel uncertainty. In com...
Publication Info
- Year
- 2004
- Type
- article
- Volume
- 27
- Issue
- 12
- Pages
- 712-719
- Citations
- 2539
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
2539
OpenAlex
Cite This
David C. Knill,
Alexandre Pouget
(2004).
The Bayesian brain: the role of uncertainty in neural coding and computation.
Trends in Neurosciences
, 27
(12)
, 712-719.
https://doi.org/10.1016/j.tins.2004.10.007
Identifiers
- DOI
- 10.1016/j.tins.2004.10.007