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Institution

Australian National University

EducationCanberra, Australian Capital Territory, Australia
About: Australian National University is a education organization based out in Canberra, Australian Capital Territory, Australia. It is known for research contribution in the topics: Population & Galaxy. The organization has 34419 authors who have published 109261 publications receiving 4315448 citations. The organization is also known as: The Australian National University & ANU.
Topics: Population, Galaxy, Stars, Zircon, Politics


Papers
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Proceedings ArticleDOI
15 Jun 2019
TL;DR: In this paper, a category-level adversarial network is proposed to enforce local semantic consistency during the trend of global alignment, where the weight of the adversarial loss for well aligned features is reduced, while increasing the strength of adversarial force for poorly aligned features.
Abstract: We consider the problem of unsupervised domain adaptation in semantic segmentation. The key in this campaign consists in reducing the domain shift, i.e., enforcing the data distributions of the two domains to be similar. A popular strategy is to align the marginal distribution in the feature space through adversarial learning. However, this global alignment strategy does not consider the local category-level feature distribution. A possible consequence of the global movement is that some categories which are originally well aligned between the source and target may be incorrectly mapped. To address this problem, this paper introduces a category-level adversarial network, aiming to enforce local semantic consistency during the trend of global alignment. Our idea is to take a close look at the category-level data distribution and align each class with an adaptive adversarial loss. Specifically, we reduce the weight of the adversarial loss for category-level aligned features while increasing the adversarial force for those poorly aligned. In this process, we decide how well a feature is category-level aligned between source and target by a co-training approach. In two domain adaptation tasks, i.e., GTA5 -> Cityscapes and SYNTHIA -> Cityscapes, we validate that the proposed method matches the state of the art in segmentation accuracy.

478 citations

Journal ArticleDOI
TL;DR: An analysis has been made in anaesthetised cats of the depression by glycine and related amino acids of the firing of spinal dorsal horn interneurones, Renshaw cells and cortical neurones, and the involvement of a glycine-like amino acid as a major spinal inhibitory transmitter is discussed.
Abstract: An analysis has been made in anaesthetised cats of the depression by glycine and related amino acids of the firing of spinal dorsal horn interneurones, Renshaw cells and cortical neurones. In general, electrophoretically administered glycine was a more potent depressant of interneurones than GABA. The reverse was true for cortical neurones, whereas these two amino acids were approximately equally effective upon Renshaw cells. Strychnine blocked the depressant action of α- and β-amino acids, but not that of γ- and higher ω-amino acids. Only convulsants having a strychnine-like effect on spinal post-synaptic inhibition blocked the action of glycine. The depression of spinal neurones produced by glycine or GABA was not affected by structural analogues of glycine and GABA that were not depressants, or by substances influencing amino acid transport systems. Some evidence was obtained for the enzymic inactivation of electrophoretically administered glycine in spinal tissue. The results are discussed in terms of the involvement of a glycine-like amino acid as a major spinal inhibitory transmitter.

478 citations

Book ChapterDOI
01 Jan 2012

478 citations

Journal ArticleDOI
24 Aug 2018-Science
TL;DR: It is shown that to mitigate global water scarcity, increases in IE must be accompanied by robust water accounting and measurements, a cap on extractions, an assessment of uncertainties, the valuation of trade-offs, and a better understanding of the incentives and behavior of irrigators.
Abstract: S.A.W. was supported by the Australian Research Council project FT140100773; C.R. was supported by the CGIAR Research Program on Water, Land, and Ecosystems; and F.M. was supported by the Agence Nationale de la Recherche (ANR) AMETHYST project (ANR-12 TMED-0006-01).

477 citations

Journal ArticleDOI
TL;DR: The authors argue that the literatures on policy transfer and policy diffusion are complimentary, but need to focus more clearly on five key issues drawing insights from both literatures, including the changing interactions between the various mechanisms involved in diffusion/transfer.
Abstract: This article argues that the literatures on policy transfer and policy diffusion are complimentary, but need to focus more clearly on five key issues drawing insights from both literatures. First, work in each area can benefit from a greater focus on the changing interactions between the various mechanisms involved in diffusion/transfer. Second, the diffusion literature privileges structure, while the transfer literature privileges agency, but we need an approach which recognizes the dialectical relationship between the two. Third, the diffusion literature concentrates on pattern-finding, while the transfer literature examines process-tracing, but any full explanation of transfer/diffusion needs to do both. Fourth, both literatures suffer from skewed case selection with, in particular, too little attention paid to developing countries. Finally, while both literatures need to be interested in whether diffusion/transfer is likely to be successful/unsuccessful, neither considers any criteria that might be us...

477 citations


Authors

Showing all 34925 results

NameH-indexPapersCitations
Cyrus Cooper2041869206782
Nicholas G. Martin1921770161952
David R. Williams1782034138789
Krzysztof Matyjaszewski1691431128585
Anton M. Koekemoer1681127106796
Robert G. Webster15884390776
Ashok Kumar1515654164086
Andrew White1491494113874
Bernhard Schölkopf1481092149492
Paul Mitchell146137895659
Liming Dai14178182937
Thomas J. Smith1401775113919
Michael J. Keating140116976353
Joss Bland-Hawthorn136111477593
Harold A. Mooney135450100404
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023280
2022773
20215,261
20205,464
20195,109
20184,825