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NIPS
2007
15 years 5 months ago
Variational Inference for Diffusion Processes
Diffusion processes are a family of continuous-time continuous-state stochastic processes that are in general only partially observed. The joint estimation of the forcing paramete...
Cédric Archambeau, Manfred Opper, Yuan Shen...
UAI
2008
15 years 5 months ago
Sampling First Order Logical Particles
Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fu...
Hannaneh Hajishirzi, Eyal Amir
WSC
2004
15 years 5 months ago
Experimental Performance Evaluation of Histogram Approximation for Simulation Output Analysis
We summarize the results of an experimental performance evaluation of using an empirical histogram to approximate the steady-state distribution of the underlying stochastic proces...
E. Jack Chen, W. David Kelton
ICML
2010
IEEE
15 years 5 months ago
Learning Deep Boltzmann Machines using Adaptive MCMC
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
Ruslan Salakhutdinov
JFR
2008
76views more  JFR 2008»
15 years 4 months ago
Robust trajectory tracking for a reversing tractor trailer
Tractor-trailer reversing is a classical non-linear control problem in which many of the solutions proposed in the literature perform poorly in the presence of real-world constrai...
Cédric Pradalier, Kane Usher