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Institution

University of Waterloo

EducationWaterloo, Ontario, Canada
About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a semi-empirical method for the prediction of intermolecular forces was proposed for systems with a small number of electrons and leads to the conclusion that those systems behave as the internal atomic correlation energy was almost independent from the interatomic distance.

459 citations

Journal ArticleDOI
TL;DR: The key idea is to use point estimates based on Poisson models and to develop robust variance estimates that are valid more generally and illustrated on reliability and warranty data.
Abstract: Nelson discussed a method of estimating the cumulative mean function for identically distributed processes of recurrent events. We show that a similar approach can be used with more general models, including regression, The key idea is to use point estimates based on Poisson models and to develop robust variance estimates that are valid more generally. The methods are illustrated on reliability and warranty data.

458 citations

Journal ArticleDOI
TL;DR: This paper investigates the error rate performance of FSO systems for K-distributed atmospheric turbulence channels and discusses potential advantages of spatial diversity deployments at the transmitter and/or receiver, and presents efficient approximated closed-form expressions for the average bit-error rate (BER) of single-input multiple-output (SIMO) FSO Systems.
Abstract: Optical wireless, also known as free-space optics, has received much attention in recent years as a cost-effective, license-free and wide-bandwidth access technique for high data rates applications. The performance of free-space optical (FSO) communication, however, severely suffers from turbulence-induced fading caused by atmospheric conditions. Multiple laser transmitters and/or receivers can be placed at both ends to mitigate the turbulence fading and exploit the advantages of spatial diversity. Spatial diversity is particularly crucial for strong turbulence channels in which single-input single-output (SISO) link performs extremely poor. Atmospheric-induced strong turbulence fading in outdoor FSO systems can be modeled as a multiplicative random process which follows the K distribution. In this paper, we investigate the error rate performance of FSO systems for K-distributed atmospheric turbulence channels and discuss potential advantages of spatial diversity deployments at the transmitter and/or receiver. We further present efficient approximated closed-form expressions for the average bit-error rate (BER) of single-input multiple-output (SIMO) FSO systems. These analytical tools are reliable alternatives to time-consuming Monte Carlo simulation of FSO systems where BER targets as low as 10-9 are typically aimed to achieve.

458 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate cathodes for the Li-S cell comprised of sulfur-imbibed robust spherical carbon shells with tailored porosity that exhibit excellent cycling stability, showing how sulfur fraction (underutilization) and sulfide precipit...
Abstract: Among the most challenging issues in electrochemical energy storage is developing insightful in situ probes of redox processes for a working cell. This is particularly true for cells that operate on the basis of chemical transformations such as Li–S and Li–O2, where the factors that govern capacity and cycling stability are difficult to access owing to the amorphous nature of the intermediate species. Here, we investigate cathodes for the Li–S cell comprised of sulfur-imbibed robust spherical carbon shells with tailored porosity that exhibit excellent cycling stability. Their highly regular nanoscale dimensions and thin carbon shells allow highly uniform electrochemical response and further enable direct monitoring of sulfur speciation within the cell over the entire redox range by operando X-ray absorption spectroscopy on the S K-edge. The results reveal the first detailed evidence of the mechanisms of sulfur redox chemistry on cycling, showing how sulfur fraction (under-utilization) and sulfide precipit...

457 citations

Posted Content
TL;DR: This work introduces several ways of regularizing the objective, which can dramatically stabilize the training of GAN models and shows that these regularizers can help the fair distribution of probability mass across the modes of the data generating distribution, during the early phases of training and thus providing a unified solution to the missing modes problem.
Abstract: Although Generative Adversarial Networks achieve state-of-the-art results on a variety of generative tasks, they are regarded as highly unstable and prone to miss modes. We argue that these bad behaviors of GANs are due to the very particular functional shape of the trained discriminators in high dimensional spaces, which can easily make training stuck or push probability mass in the wrong direction, towards that of higher concentration than that of the data generating distribution. We introduce several ways of regularizing the objective, which can dramatically stabilize the training of GAN models. We also show that our regularizers can help the fair distribution of probability mass across the modes of the data generating distribution, during the early phases of training and thus providing a unified solution to the missing modes problem.

456 citations


Authors

Showing all 36498 results

NameH-indexPapersCitations
John J.V. McMurray1781389184502
David A. Weitz1781038114182
David Taylor131246993220
Lei Zhang130231286950
Will J. Percival12947387752
Trevor Hastie124412202592
Stephen Mann12066955008
Xuan Zhang119153065398
Mark A. Tarnopolsky11564442501
Qiang Yang112111771540
Wei Zhang112118993641
Hans-Peter Seidel112121351080
Theodore S. Rappaport11249068853
Robert C. Haddon11257752712
David Zhang111102755118
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023213
2022701
20215,359
20205,388
20195,200