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» Neural Dynamics with Stochasticity
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101
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NN
2006
Springer
100views Neural Networks» more  NN 2006»
15 years 19 days ago
Perceiving the unusual: Temporal properties of hierarchical motor representations for action perception
Recent computational approaches to action imitation have advocated the use of hierarchical representations in the perception and imitation of demonstrated actions. Hierarchical re...
Yiannis Demiris, Gavin Simmons
JMM2
2007
183views more  JMM2 2007»
15 years 17 days ago
A Chaos Theoretic Analysis of Motion and Illumination in Video Sequences
— Accurate and robust image motion detection has been of substantial interest in the image processing and computer vision communities. Unfortunately, no single motion detection a...
Michael E. Farmer
112
Voted
PAMI
2010
113views more  PAMI 2010»
14 years 11 months ago
Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents
—We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic...
Iulian Pruteanu-Malinici, Lu Ren, John William Pai...
244
Voted
ICDE
2004
IEEE
259views Database» more  ICDE 2004»
16 years 2 months ago
Querying about the Past, the Present, and the Future in Spatio-Temporal
Moving objects (e.g., vehicles in road networks) continuously generate large amounts of spatio-temporal information in the form of data streams. Efficient management of such strea...
Jimeng Sun, Dimitris Papadias, Yufei Tao, Bin Liu
106
Voted
ICML
2008
IEEE
16 years 1 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh