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Field of Research : Probability Theory
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  • Researchers (19)
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  • Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE210101323

    Funder
    Australian Research Council
    Funding Amount
    $345,448.00
    Summary
    Random tensors and random matrices: interactions and applications. This project aims at improving knowledge on probabilistic objects having applications in, for instance, mathematical-physics, statistical physics, quantum gravity and data science. In doing so, we expect to produce new mathematical results by building upon both classical approaches and innovative ones. In particular, on one hand, the extension of classical graphical methods will be developed and, on another hand, generalized prob .... Random tensors and random matrices: interactions and applications. This project aims at improving knowledge on probabilistic objects having applications in, for instance, mathematical-physics, statistical physics, quantum gravity and data science. In doing so, we expect to produce new mathematical results by building upon both classical approaches and innovative ones. In particular, on one hand, the extension of classical graphical methods will be developed and, on another hand, generalized probability theories will be used to provide new insights. The expected outcomes include a better understanding of the generic properties of quantum states. This should significantly benefit to mathematicians and physicists whose models use those objects and may impact the broader community of engineers and technicians.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE210101352

    Funder
    Australian Research Council
    Funding Amount
    $330,000.00
    Summary
    Inverting the Signature Transform for Rough Paths and Random Processes. The signature transform provides an effective summary of the essential information encoded in multidimensional paths that are highly oscillatory and involve complicated randomness. The main goal of this project is to develop new algorithmic methods to reconstruct rough paths and random processes from the signature transform at various quantitative levels. This project expects to make theoretical breakthrough on the significa .... Inverting the Signature Transform for Rough Paths and Random Processes. The signature transform provides an effective summary of the essential information encoded in multidimensional paths that are highly oscillatory and involve complicated randomness. The main goal of this project is to develop new algorithmic methods to reconstruct rough paths and random processes from the signature transform at various quantitative levels. This project expects to make theoretical breakthrough on the significant open problem of signature inversion, thereby advancing knowledge in the areas of rough path theory and stochastic analysis. The newly developed methods will be utilised in combination with the emerging signature-based approach to study important problems in financial data analysis and visual speech recognition.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190100977

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    Hypergraph models for complex discrete systems. This project aims to better understand the structure and properties of very large hypergraphs of various kinds. Hypergraphs are very general mathematical objects which can be used to model complex discrete systems. They arise naturally in many areas such as ecology, chemistry and computer science. Despite this, our theoretical understanding of very large, or random, hypergraphs lags far behind the intensely-studied special case of graphs. This proj .... Hypergraph models for complex discrete systems. This project aims to better understand the structure and properties of very large hypergraphs of various kinds. Hypergraphs are very general mathematical objects which can be used to model complex discrete systems. They arise naturally in many areas such as ecology, chemistry and computer science. Despite this, our theoretical understanding of very large, or random, hypergraphs lags far behind the intensely-studied special case of graphs. This project will answer many fundamental questions about large, random hypergraphs. The expected outcomes of the project also include new tools for working with hypergraphs, such as efficient algorithms for sampling hypergraphs. These outcomes will benefit researchers who use hypergraphs in their work and will enhance Australia's reputation for research in this area.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220100973

    Funder
    Australian Research Council
    Funding Amount
    $410,000.00
    Summary
    New universality in stochastic systems. This project aims to uncover new analyses and effects in the complex behaviour of non-linear systems with random noise. Many systems originate near an unstable equilibrium. This project will develop a new mathematical theory that establishes a universality in the way the long term effect of noise expresses itself as random initial conditions in the dynamics. It will fill gaps in Mathematics and make refinements to existing fundamental scientific laws by in .... New universality in stochastic systems. This project aims to uncover new analyses and effects in the complex behaviour of non-linear systems with random noise. Many systems originate near an unstable equilibrium. This project will develop a new mathematical theory that establishes a universality in the way the long term effect of noise expresses itself as random initial conditions in the dynamics. It will fill gaps in Mathematics and make refinements to existing fundamental scientific laws by including random initial conditions as predicted by our theory. This will advance our understanding of complex systems subjected to noise and will provide significant benefits in the scientific discoveries in Biology, Ecology, Physics and other Sciences where such systems are frequently met.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200100896

    Funder
    Australian Research Council
    Funding Amount
    $427,008.00
    Summary
    How to beat model uncertainty with more information. Experience of the 2008 financial crisis exposed a weakness in our over-reliance on mathematical models. The main aim of this project is to develop mathematical tools to investigate the role of information in reducing model uncertainty. The project will undertake pressing research in robust finance, which is now one of the most active and dynamic topics in financial mathematics. It expects to quantify the value of information under uncertainty .... How to beat model uncertainty with more information. Experience of the 2008 financial crisis exposed a weakness in our over-reliance on mathematical models. The main aim of this project is to develop mathematical tools to investigate the role of information in reducing model uncertainty. The project will undertake pressing research in robust finance, which is now one of the most active and dynamic topics in financial mathematics. It expects to quantify the value of information under uncertainty in mathematical modelling. It will generate new knowledge in probability theory and stochastic processes providing a significant mathematical contribution in its own right.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200101467

    Funder
    Australian Research Council
    Funding Amount
    $419,778.00
    Summary
    The geometric structure of spatial noise. Spatial noise is ubiquitous in nature and science: as interference in medical imaging, in oceanography, in the modelling of telecommunication networks etc. Despite this diversity of sources, spatial noise can be studied in a unified way by considering mathematical models that capture its essential features. This project aims to study spatial noise by analysing its geometric structure, for instance by considering the number of contour lines of the noise, .... The geometric structure of spatial noise. Spatial noise is ubiquitous in nature and science: as interference in medical imaging, in oceanography, in the modelling of telecommunication networks etc. Despite this diversity of sources, spatial noise can be studied in a unified way by considering mathematical models that capture its essential features. This project aims to study spatial noise by analysing its geometric structure, for instance by considering the number of contour lines of the noise, and the way these lines connect different regions of space. The project further aims to apply this analysis to construct statistical tests that can distinguish different classes of spatial noise, with potential applications across all of the disciplines mentioned above.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT170100409

    Funder
    Australian Research Council
    Funding Amount
    $960,000.00
    Summary
    Epidemics in large populations: long-term and near-critical behaviour. The project aims to prove qualitative and quantitative results concerning aspects of the long-term behaviour of near-critical epidemics, including the probability and duration of a large outbreak, and the total number of people infected. This project is a theoretical study of stochastic models of epidemics in large populations. The project will focus on emerging epidemics, where the average number of contacts, infection and r .... Epidemics in large populations: long-term and near-critical behaviour. The project aims to prove qualitative and quantitative results concerning aspects of the long-term behaviour of near-critical epidemics, including the probability and duration of a large outbreak, and the total number of people infected. This project is a theoretical study of stochastic models of epidemics in large populations. The project will focus on emerging epidemics, where the average number of contacts, infection and recovery rates are such that the basic reproduction number of the disease is near the critical value 1. The project will plan to both analyse particular epidemic models and develop new methodologies applicable in broader contexts. The mathematical predictions will be tested through simulations and comparison to real-world data. The significant outcome of the project should be the advancement in mathematical understanding of infectious disease spread, eventually leading to improved epidemic surveillance and control, and resulting in more effective protection of public health, improved quality of life, and obvious economic benefits.
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    Showing 1-7 of 7 Funded Activites

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