Items with category:D2i Seminar

2021-08: Reflections on Interdisciplinary Research Practice

Date: 27/08/2021, 11-12 am Title: Heart rate variability (HRV) Analysis using Entropy Methods Abstract: Discussing opportunities and challenges when conducting interdisciplinary research. Speaker: Dr Birgit Muskat, Australian National University. Dr Muskat is the Deputy Director, Research School of Management, Higher Degree Research at the College of Business and Economics at ANU. Her research interests include […]

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2021-08: Deep Graph Contrastive Learning

Date: 06/08/2021, 2-3 pm  Title: Deep Graph Contrastive Learning  Abstract: Self-supervised learning (SSL) has been extensively studied to alleviate the label sparsity problem in deep models. Recent self-supervised learning techniques are converging around the central theme of Contrastive Learning (CL), which aims to maximize the consistency of representations under multiple views of the input data. […]

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2021-08: Heart rate variability (HRV) Analysis using Entropy Methods

Date: 05/08/2021, 2-3 pm  Title: Heart rate variability (HRV) Analysis using Entropy Methods Abstract: Heart rate variability (HRV), a variation in the time interval between successive heart beats, is a prognostic indicator of various physiological conditions, such as disease, stress, aging, fitness, and gender. Every physiological condition is linked to a change in heart rate […]

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2021-07: Discriminative Representation for Topological Data Analysis

Date: 30/07/2021, 10-11am, Friday Title: Discriminative Representation for Topological Data Analysis Abstract: Topological data analysis (TDA) extracts the topological features that are complementary to statistical quantities, which has been found in many applications in computer vision. In TDA, the persistence diagram (PD) is a favored tool for describing topological features, such as the shape of […]

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2021-06: Are SVMs still of interest when meeting deep neural networks

Date and time: 16 June, 2021, Wednesday 1pm in Melbourne time (11am in Perth Time). Title: Are SVMs still of interest when meeting deep neural networks Abstract: Deep neural networks (DNNs) have been a standard recipe for creating state-of-the-art solutions. As a result, models like Support Vector Machines (SVMs) have been overlooked. While the results […]

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2020-11: Modelling the seeding and spread of pathology via brain networks in progressive neurodegenerative disorders

Dear Colleagues and HDR Students, You are invited to attend the following D2I Seminar, as part of the School of IT Seminar Series: Date: Friday 20 November Time: 11.00am-12.00pm Join: https://deakin.zoom.us/j/99464011675?pwd=ejI3L05OUHFMUld0bjZuUVFjakZvZz09&from=addon Meeting ID: 994 6401 1675 Password: 151880 Speaker: Dr Govinda Poudel (Mary Mackillop Institute for Health Research, Melbourne) Abstract: The human brain is a complex […]

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