Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ale...
This paper breaks with the common practice of using a joint state space representation and performing the joint data association in multi-object tracking. Instead, we present an i...
A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given ...
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...