Events
Calendar of Events
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1 event,ECSSC2021 Video Competition Submissions will open shortly for ECSSC2021 Video Competition. Working on any research? Put a video together and demonstrate your ability to concisely disseminate your research to a wider audience. Any student or early career statistician (within 5 years of graduation) in a statistics related field is welcome to enter the competition (sorry… |
2 events,ACEMS Impact Workshop for Researchers and Students ACEMS is pleased to invite you to attend a workshop on the topic of Research Impact, tailored for the mathematical sciences. It will be co-facilitated by Impact Research Academy and ACEMS. Workshop Details - Please RSVP (for Zoom Links) Aims and Benefits of Workshop This workshop is designed,… |
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2 events,Australian and New Zealand Statistical Conference (ANZSC2021) The organising committee warmly invites you to the 2021 Australian and New Zealand Statistical Conference, which will take place online from the 5th to the 9th July 2021. This conference brings together three leading statistical communities – the Statistical Society of Australia, the New Zealand Statistical Association – and the Australian…
$200.00
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2 events,2021 AMSI Winter School on Statistical Data Science AMSI and Queensland University of Technology are proud to present the 2021 Winter School on Statistical Data Science from 12-23 July. For the first time, the program will be hosted virtually with options for students to attend event hubs in selected states. Boasting an impressive speaker line-up,… |
5 events,The first AI4PAN seminar speaker will be Chris Rackauckas (MIT) YouTube Recording Title: Learning Epidemic Models That Extrapolate. Abstract: Modern techniques of machine learning are uncanny in their ability to automatically learn predictive models directly from data. However, they do not tend to work beyond their original training dataset. Mechanistic models utilize characteristics of the…
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ACEMS Virtual Public Lecture - A Song of Wind & Fire: a statistical journey through an uncertain world In this lecture, ACEMS Associate Investigator Dr Rachael Quill will explore how shedding light on the uncertainties of wind flow across the environment can support informed decision-making in bushfire management and renewable energy generation. The weather and…
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A Celebration of Mathematics – Diversity in STEM AMSI welcomes all students, researchers and professionals with an interest in STEM to join the team for a relaxed evening of talks… |
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The Statistical Society of Australia and he Early Career Student Statistician Conference 2021 are offering this workshop on Convex Optimization for Statistical and Machine Learning with CVXR. Optimization plays an important role in fitting many statistical models. Some examples include least squares, ridge and lasso regression, Huber regression, and support vector machines. CVXR is an… |
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The Statistical Society of Australia and the Early Career and Student Statistician Conference are offering their 2nd short course leading up to the conference, to be held virtually on 25 Jul 2021, 11:00 AM - 3:00 PM AEST. About the short course: As modern data applications become complex in size and structure, identifying the underlying… |
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Early Career and Student Statistician Conference 2021 (formerly Young Statisticians Conference) The Early Career & Student Statisticians Conference (ECSSC) 2021 will be held from 26 July to 1 August 2021. We are delighted to announce that we will be holding our conference virtually! ECSSC2021 will bring together the best students and early-career professionals in statistics…
$95.00
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Speaker: Dr Kirsty Short, The University of Queensland YouTube Recording Title: The role of children in the spread of SARS-CoV-2 Abstract: The role of children in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains highly controversial. To address this issue, we performed a meta-analysis of the published literature on household SARS-CoV-2 transmission… |
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Data Science Under the Hood: Manifold Learning This talk introduces Manifold Learning, the technique to uncover the intrinsic shape of the original data. We also discuss how different manifold learning paradigms can be designed to be incorporated to a dimensionality reduction technique to learn the accurate low-dimensional data representation. Register now |
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