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ICMLA
2010
15 years 5 months ago
A Probabilistic Graphical Model of Quantum Systems
Quantum systems are promising candidates of future computing and information processing devices. In a large system, information about the quantum states and processes may be incomp...
Chen-Hsiang Yeang
CVPR
2011
IEEE
15 years 3 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
TIST
2011
136views more  TIST 2011»
15 years 2 months ago
Probabilistic models for concurrent chatting activity recognition
Recognition of chatting activities in social interactions is useful for constructing human social networks. However, the existence of multiple people involved in multiple dialogue...
Jane Yung-jen Hsu, Chia-chun Lian, Wan-rong Jih
ICML
2005
IEEE
16 years 8 months ago
Variational Bayesian image modelling
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
RECOMB
2004
Springer
16 years 7 months ago
Learning Regulatory Network Models that Represent Regulator States and Roles
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Keith Noto, Mark Craven