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We characterize the complete monotonicity of the Kilbas-Saigo function on the negative half-line. We also provide the exact asymptotics at -infinity, and uniform hyperbolic bounds are derived. The same questions are addressed for the classical Le Roy funct ...
When learning skills from demonstrations, one is often required to think in advance about the appropriate task representation (usually in either operational or configuration spaces). We here propose a probabilistic approach for simultaneously learning and ...
Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool ...
We adopt an innovation-driven framework and investigate the sparse/compressible distributions obtained by linearly measuring or expanding continuous-domain stochastic models. Starting from the first principles, we show that all such distributions are neces ...
In imitation learning, multivariate Gaussians are widely used to encode robot behaviors. Such approaches do not provide the ability to properly represent end-effector orientation, as the distance metric in the space of orientations is not Euclidean. In thi ...
In this thesis, we develop methods for modeling route choice behavior using smartphone data. The developing global positioning system (GPS) technology and the popularity of smartphones have revolutionized the revealed preference route choice data collectio ...
This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variables. The algorithm is based on an incremental compilation of formulas into decision diagr ...
This paper presents the analysis of inductive links for remote powering of implantable devices and a method to improve the power link efficiency by modifying the geometrical parameters of planar spiral inductors. The analysis of the inductive links include ...
We present a probabilistic architecture for solving generically the problem of extracting the task constraints through a Programming by Demonstration (PbD) framework and for generalizing the acquired knowledge to various situations. In previous work, we pr ...
Probabilistic predictions are becoming increasingly popular in hydrology. Equally important are methods to test such predictions, given the topical debate on uncertainty analysis in hydrology. Also in the special case of hydrological forecasting, there is ...
