Learning invariant features using the Transformed Indian Buffet Process

No abstract is available for this paper.

• Publication year

  2010

• Venue

  Neural Information Processing Systems

• Publication date

  2010-12-06

• Fields of study

  Computer Science

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Unsupervised Learning

  2018cited by this paper
• Bayesian Nonparametric Learning : Expressive Priors for Intelligent Systems

  2010cited by this paper
• The effect of distributional information on feature learning

  2009cited by this paper
• Analyzing human feature learning as nonparametric Bayesian inference

  2008cited by this paper
• Bayesian learning of visual chunks by human observers

  2008cited by this paper
• A Non-Parametric Bayesian Method for Inferring Hidden Causes

  2006cited by this paper
• Infinite latent feature models and the Indian buffet process

  2005influential reference
• Describing Visual Scenes using Transformed Dirichlet Processes

  2005cited by this paper
• Unsupervised learning in neural computation

  2002cited by this paper
• Transactions on pattern analysis and machine

  2002cited by this paper
• Factorial Learning and the EM Algorithm

  1994cited by this paper
• Preface to S. Geman and D. Geman, “Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images”

  1987cited by this paper
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

  1984cited by this paper
• The Analysis of Sensations.

  1916cited by this paper
• PSYCHOLOGICAL SCIENCE Research Article UNSUPERVISED STATISTICAL LEARNING OF HIGHER-ORDER SPATIAL STRUCTURES FROM VISUAL SCENES

  year unknowninfluential reference

• Paradise of Forking Paths: Revisiting the Adaptive Data Analysis Problem

  2025cites this paper
• Embedding Gestalt Principles to Hierarchical Distance Dependent Nonparametric Bayesian Model for Video Segmentation

  2019cites this paper
• Content-Style Decomposition: Representation Discovery and Applications

  2018cites this paper
• Edinburgh Research Explorer The Child as Econometrician

  2018cites this paper
• A Survey of Inductive Biases for Factorial Representation-Learning

  2016cites this paper
• The Oxford Handbook of Computational and Mathematical Psychology

  2015influential citation
• Structure and Flexibility in Bayesian Models of Cognition

  2015influential citation
• The Child as Econometrician: A Rational Model of Preference Understanding in Children

  2014cites this paper
• child as a rational model of preference understanding in children.

  2014cites this paper
• The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

  2013cites this paper
• ( YIP-10 ) FAST , FLEXIBLE , RATIONAL INDUCTIVE INFERENCE

  2013cites this paper
• A nonparametric Bayesian framework for constructing flexible feature representations.

  2013cites this paper
• A Bayesian Model of Rule Induction in Raven's Progressive Matrices

  2012cites this paper
• Nonparametric Bayesian Models for Unsupervised Scene Analysis and Reconstruction

  2012cites this paper
• Learning Image Attributes using the Indian Buffet Process

  2012cites this paper
• Modeling Images using Transformed Indian Buffet Processes

  2012cites this paper
• Bayesian Nonparametric Latent Feature Models

  2011influential citation
• An ideal observer model for identifying the reference frame of objects

  2011cites this paper
• A rational model of the effects of distributional information on feature learning.

  2011cites this paper