Bloom, Joshua S, Khan, Zia, Kruglyak, Leonid, Singh, Mona, Caudy, Amy A
Abstract Background High-throughput cDNA synthesis and sequencing of poly(A)-enriched RNA is rapidly emerging as a technology competing to replace microarrays as a quantitative platform for measuring...
Khan, Zia, Bloom, Joshua S., Kruglyak, Leonid, Singh, Mona
Motivation: High-throughput sequencing technologies place ever increasing demands on existing algorithms for sequence analysis. Algorithms for computing maximal exact matches (MEMs) between sequences...
Zia Khan, Tucker Balch, Frank Dellaert
In several multitarget tracking applications a target may return more than one measurement per target, and interacting targets may return multiple merged measurements between targets. Existing...
Zia Khan, Rebecca A. Herman, Kim Wallen, Tucker Balch
Outdoor 3-d Tracking 2 Studies of the navigational abilities of nonhuman primates have largely been limited to what could be described by an observer with a pen and paper. Consequently, we have...
MCMC-based particle filtering for tracking a variable number of interacting targets (2005)
Zia Khan, Tucker Balch, Frank Dellaert
We describe a particle filter that effectively deals with interacting targets- targets that are influenced by the proximity and/or behavior of other targets. The particle filter includes a Markov...
MCMC-based particle filtering for tracking a variable number of interacting targets (2005)
Zia Khan, Tucker Balch, Frank Dellaert
Abstract—We describe a particle filter that effectively deals with interacting targets—targets that are influenced by the proximity and/or behavior of other targets. The particle filter includes...
Multitarget tracking with split and merged measurements (2005)
Zia Khan, Tucker Balch, Frank Dellaert
In many multitarget tracking applications in computer vision, a detection algorithm provides locations of potential targets. Subsequently, the measurements are associated with previously estimated...
MCMC-based particle filtering for tracking a variable number of interacting targets (2005)
Zia Khan, Tucker Balch, Frank Dellaert
We describe a particle filter that effectively deals with interacting targets- targets that are influenced by the proximity and/or behavior of other targets. The particle filter includes a Markov...
Robust Generative Subspace Modeling: The Subspace t Distribution (2004)
Linear latent variable models such as statistical factor analysis (SFA) and probabilistic principal component analysis (PPCA) assume that the data are distributed according to a multivariate...
An MCMC-based Particle Filter (2004)
For Tracking Multiple, Zia Khan, Tucker Balch, Frank Dellaert
We describe a Markov chain Monte Carlo based particle filter that e#ectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such...
A Rao-Blackwellized Particle Filter for EigenTracking (2004)
Zia Khan, Tucker Balch, Frank Dellaert
Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black's influential paper on EigenTracking, they were successfully applied in tracking. For...
Robust Generative Subspace Modeling: The Subspace t Distribution (2004)
Linear latent variable models such as statistical factor analysis (SFA) and probabilistic principal component analysis (PPCA) assume that the data are distributed according to a multivariate...
Robust Generative Subspace Modeling: The Subspace t Distribution (2004)
Linear latent variable models such as statistical factor analysis (SFA) and probabilistic principal component analysis (PPCA) assume that the data are distributed according to a multivariate...
An MCMC-based Particle Filter for Tracking Multiple Interacting Targets (2003)
Khan, Zia, Balch, Tucker, Dellaert, Frank
We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such...
An MCMC-based Particle Filter For Tracking Multiple Interacting Targets (2003)
Zia Khan, Tucker Balch, Frank Dellaert
We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such...
An MCMC-based Particle Filter for Tracking Multiple Interacting Targets (2003)
Khan, Zia, Balch, Tucker, Dellaert, Frank
We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such...
Balch, Tucker, Dellaert, Frank, Khan, Zia
We describe a multiple hypothesis particle filter for tracking targets that will be influenced by the proximity and/or behavior of other targets. Our contribution is to show how a Markov random field...
Protein quantification across hundreds of experimental conditions
Khan, Zia, Bloom, Joshua S., Garcia, Benjamin A., Singh, Mona, Kruglyak, Leonid
Quantitative studies of protein abundance rarely span more than a small number of experimental conditions and replicates. In contrast, quantitative studies of transcript abundance often span hundreds...