- AdaBoost Learning for Detecting and Recognizing Department of Statistics
- Latent Hierarchical Structural Learning for Object Detection Long (Leo) Zhu1
- Unsupervised Learning of Probabilistic Grammar-Markov Models for Object Categories
- Int'l J. of Computer Vision, Marr Prize Issue, 2005. Image Parsing: Unifying Segmentation, Detection, and
- Active Skeleton for Non-rigid Object Detection Huazhong Univ. of Sci.&Tech.
- A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci
- Bayesian Generic Priors for Causal Learning Hongjing Lu, Alan L. Yuille, Mimi Liljeholm, Patricia W. Cheng, and Keith J. Holyoak
- The Concave-Convex Procedure (CCCP). Alan Yuille
- Image Parsing: Unifying Segmentation, Detection, and Recognition
- Image Parsing: Segmentation, Detection, and Recognition.
- Efficient Coding of Visual Scenes by Grouping and Segmentation: Theoretical Principles and Biological
- Unsupervised Learning of Object Deformation Iasonas Kokkinos
- The Convergence of Contrastive Divergences Alan Yuille
- CCCP Algorithms to Minimize the Bethe and Kikuchi Free Energies: Convergent
- Shape matching and registration by data-driven EM Zhuowen Tu a,*, Songfeng Zheng b
- Detecting Object Boundaries using Low-,Middle-, and High-Level Information.
- A Time-Efficient Cascade for Real-Time Object Detection: With applications for the visually impaired.
- Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
- Structure-Perceptron Learning of a Hierarchical Log-Linear Model Long (Leo) Zhu
- Max Margin AND/OR Graph Learning for Parsing the Human Body Long (Leo) Zhu
- Motion integration using competitive priors , Hongjing Lu2
- Model selection and velocity estimation using novel priors for motion patterns
- The perceived motion of a stereokinetic stimulus Bas Rokers a
- Motion Estimation by Swendsen-Wang Cuts Adrian Barbu
- Compositional Noisy-Logical Learning Alan Yuille yuille@stat.ucla.edu
- Sequential Causal Learning in Humans and Rats Hongjing Lu (hongjing@ucla.edu)
- Technical Introduction: A primer on probabilistic
- The Noisy-Logical Distribution and its Application to Causal Inference
- Modeling Causal Learning Using Bayesian Generic Priors on Generative and Preventive Powers
- Probability Primer 1 Running head: PROBABILITY PRIMER
- The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters.
- Detection and Segmentation of Pathological Structures by the Extended Graph-Shifts Algorithm
- Modeling the spacing effect in sequential category Hongjing Lu
- Human and Ideal Observers for Detecting Image Alan Yuille
- A Statistical Approach to Multi-Scale Edge Detection. S.M. Konishi
- Algorithms from Statistical Physics for Generative Models of Images.
- The Concave-Convex Procedure (CCCP) A. L. Yuille and Anand Rangarajan
- The Concave-Convex Procedure (CCCP) A. L. Yuille and Anand Rangarajan
- Recursive Segmentation and Recognition Templates for 2D Parsing
- Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence
- Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing
- The DLR Hierarchy of Approximate Inference Michal Rosen-Zvi
- Part and Appearance Sharing: Recursive Compositional Models for Multi-View Multi-Object Detection
- Unsupervised Learning of Probabilistic Object Models (POMs) for Object Classification,
- Bottom-Up and Top-Down Object Detection using Primal Sketch Features and Graphical Models
- A Hierarchical Compositional System for Rapid Object Detection.
- Statistical Edge Detection: Learning and Evaluating S.M. Konishi
- A Bayesian Network for Relational Shape Matching Anand Rangarajan
- IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007 541 Automated Extraction of the Cortical Sulci Based on
- Ideal Observers for Detecting Human Motion: Correspondence Noise.
- Unsupervised Learning of Probabilistic Object Models (POMs) for Object Classification, Segmentation and Recognition
- Manhattan World James Coughlan
- Manuscript submitted to IEEE Transactions on Medical Imaging. Do not distribute.
- Augmented Rescorla-Wagner and Maximum Likelihood Estimation.
- Object Perception as Bayesian Inference 1 Object Perception as Bayesian Inference
- Bayesian Models of Judgments of Causal Strength: A Comparison Hongjing Lu (hongjing@hkucc.hku.hk)
