We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
In this paper, we address the modeling and analysis issues associated with a generic theater level campaign where two adversaries pit their military resources against each other ov...
Debasish Ghose, M. Krichman, Jason L. Speyer, Jeff...
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
We present a new algorithm to jointly track multiple objects in multi-view images. While this has been typically addressed separately in the past, we tackle the problem as a single...
Laura Leal-Taixe, Gerard Pons-Moll, Bodo Rosenhahn
Motion-compensated temporal wavelet decomposition is a useful framework for fully scalable video compression schemes. In this paper we propose a new approach to reduce the ghostin...