Applying state of the art deeplearning models to novel real world datasets gives a practical evaluation of the generalizability of these models. Of importance in this process is how sensitive the hyper parameters of such models are to novel datasets as this would affect the reproducibility of a model. We present work to characterize the hyper parameter space of an LSTM for language modeling on ...

We present herein a compilation and trend analysis of human i.v. pharmacokinetic data on 670 drugs representing, to our knowledge, the largest publicly available set of human clinical pharmacokinetic data. This data set provides the drug metabolism scientist with a robust and accurate resource suitable for a number of applications, including in silico modeling, in vitro-in vivo scaling, and phy...

In his elegant discussion, Sripada distinguishes three possible innate bases for aspects of morality: (1) certain specific principles might be innate, (2) a less simple “principles and parameters” model might apply, and (3) innate biases might have have some influence over what morality a person acquires without determining the content of that morality.1 He argues against (1) and (2) and in fav...

The use of auctions for distributing resources in competing environments has produced a large variety of auctions types and algorithms to treat them. However, auctions have some problems when faced with some real-world applications containing renewable and perishable resources. In this paper we present a mechanism to deal with such issues by dynamically configuring some of the auction parameter...

When modeling student learning, tutors that use the Knowledge Tracing framework often assume that all students have the same set of model parameters. We find that when fitting parameters to individual students, there is significant variation among the individual’s parameters. We examine if this variation is important in terms of instructional decisions by computing the difference in the expecte...

This paper concerns the reconstruction of the absorption and scattering parameters in a time-dependent linear transport equation from knowledge of angularly averaged measurements performed at the boundary of a domain of interest. We show that the absorption coefficient and the spatial component of the scattering coefficient are uniquely determined by such measurements. We obtain stability resul...

Positron annihilation Dopplerbroadening measurements were carried out on Cu-Al-Ni based alloys to which Ti, and Ti and Mn was added. The measurements reveal a drastic effect in the S-parameter behavior when the defects anneal out at the transition from martensite to the beta phase. When crossing the transition region several times, an increase of the S-parameter value is observed. This is inter...

The wave propagation in a one-dimensional nonhomogeneous medium is considered, where the wave speed and the restoring force depend on location. In the frequency domain this is equivalent to the Schrijdinger equation d2$/dx2 + k211, = k2P(x)II, + Q(x)Jt with an added potential proportional to energy. The scattering and bound-state solutions of this equation are studied and the properties of the ...

This paper concerns the reconstruction of the absorption and scattering parameters in a time-dependent linear transport equation from knowledge of angularly averaged measurements performed at the boundary of a domain of interest. We show that the absorption coefficient and the spatial component of the scattering coefficient are uniquely determined by such measurements. We obtain stability resul...

0031-9007= In this Letter, we show that upper limits on the neutrino mass translate into upper limits on the class of neutrino-matter interactions that can generate loop corrections to the neutrino mass matrix. We apply our results to and decays and derive model-independent limits on six of the ten parameters used to parametrize contributions to decay that do not belong to the standard model. T...