Výsledky vyhledávání - "Lachlan McCalman"

A Bayesian inference tool for geophysical joint inversions

Autor: Alistair Reid, Graeme Beardsmore, Simon O'Callaghan, Hugh Durrant-Whyte, Lachlan McCalman

Publikováno v: ASEG Extended Abstracts. 2016:1-10

Geophysical joint inversions seek to exploit the statistical fact that a model that simultaneously satisfies two or more independent data sets is more likely to represent geological ‘reality’ than a model that only satisfies a single data set. In

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::760372b9668d244c9930a66f1bc9f742
https://doi.org/10.1071/aseg2016ab131

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Partitioning mortality into growth-dependent and growth-independent hazards across 203 tropical tree species

Autor: Richard G. FitzJohn, Joseph S. Wright, Richard Condit, Mark Westoby, Lachlan McCalman, James S. Camac, Daniel Steinberg, Daniel S. Falster

Tree death drives population dynamics, nutrient cycling, and evolution within plant communities. Mortality variation across species is thought to be influenced by different factors relative to variation within species. The unified model provided here

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8df6185e0fa6eeaf92f2f5d2abcde606
https://europepmc.org/articles/PMC6298112/

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Unifying intra- and inter-specific variation in tropical tree mortality

Autor: Joseph S. Wright, Richard Condit, Daniel S. Falster, Daniel Steinberg, James S. Camac, Lachlan McCalman, Richard G. FitzJohn, Mark Westoby

Tree death is a fundamental process driving population dynamics, nutrient cycling, and evolution within plant communities. While past research has identified factors influencing tree mortality across a variety of scales, these distinct drivers are ye

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b133876dd3927dd1464e7e6d1c6f6160

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Using Machine Learning to Explore the Dynamics of Complex Laser Systems

Autor: Tushar Malica, Lachlan McCalman, Deborah M. Kane, J. P. Toomey, Alistair Reid

Publikováno v: Photonics and Fiber Technology 2016 (ACOFT, BGPP, NP).

Proof of principle study using a machine learning algorithm to actively sample the operating parameter space of a complex laser system, in real-time, to find the boundaries between differentiated dynamical regions efficiently.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d9486730691a46b1be2535bd3ef3b41d
https://doi.org/10.1364/acoft.2016.jt4a.18

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Real Time Relativity: Exploratory learning of special relativity

Autor: Antony C. Searle, Craig Savage, Lachlan McCalman

Publikováno v: American Journal of Physics. 75:791-798

Real Time Relativity is a computer program that lets students fly at relativistic speeds though a simulated world populated with planets, clocks, and buildings. The counterintuitive and spectacular optical effects of relativity are prominent, while s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3466df9866a4b34d9e28730f4314b6e
https://doi.org/10.1119/1.2744048

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Multi-modal estimation with kernel embeddings for learning motion models

Autor: Fabio Ramos, Lachlan McCalman, Simon O'Callaghan

Publikováno v: ICRA

We present a novel estimation algorithm for filtering and regression with a number of advantages over existing methods. The algorithm has wide application in robotics as no assumptions are made about the underlying distributions, it can represent non

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1bb71545769cb6f5ca996f91e210889c
https://doi.org/10.1109/icra.2013.6630971

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Decentralised cooperative localisation for heterogeneous teams of mobile robots

Autor: Lachlan McCalman, Timothy S. Bailey, John Vial, Mitch Bryson, Hua Mu, Hugh Durrant-Whyte

Publikováno v: ICRA

This paper presents a distributed algorithm for performing joint localisation of a team of robots. The mobile robots have heterogeneous sensing capabilities, with some having high quality inertial and exteroceptive sensing, while others have only low

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c75074a200d6c538d24e009ed6262241
https://doi.org/10.1109/icra.2011.5979850

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Bayesian filtering with wavefunctions

Autor: Hugh Durrant-Whyte, Lachlan McCalman

Publikováno v: FUSION

This paper describes a general framework for performing Bayesian filtering on probability density functions represented by the modulus squared of a wavefunction in an orthogonal function basis. The objective of this work is to find a sparse represent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::45766db1cc95406310e11ac53e4557a7
https://doi.org/10.1109/icif.2010.5711828

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