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CVPR
2011
IEEE
13 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...
ICCAD
2001
IEEE
104views Hardware» more  ICCAD 2001»
14 years 4 months ago
A Symbolic Simulation-Based Methodology for Generating Black-Box Timing Models of Custom Macrocells
We present a methodology for generating black-box timing models for full-custom transistor-level CMOS circuits. Our approach utilizes transistor-level ternary symbolic timing simu...
Clayton B. McDonald, Randal E. Bryant
ICWE
2009
Springer
14 years 2 months ago
UWE4JSF: A Model-Driven Generation Approach for Web Applications
Model-driven engineering is a promising approach, but there are still many hurdles to overcome. The tool UWE4JSF solves the hurdles for the model-driven development of web applicat...
Christian Kroiss, Nora Koch, Alexander Knapp
INFORMS
1998
142views more  INFORMS 1998»
13 years 7 months ago
Distributed State Space Generation of Discrete-State Stochastic Models
High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models often requires the generatio...
Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
AIED
2005
Springer
14 years 1 months ago
Generating Reports of Graphical Modelling Processes for Authoring and Presentation
Today's computer supported modelling environments could provide much more information about the users’ actions and problem solving processes than they usually store for late...
Lars Bollen