BEGIN:VCALENDAR
VERSION:2.0
PRODID:Ludger using PHP/v0.1
X-PUBLISHED-TTL:PT15MIN
METHOD:PUBLISH
X-WR-CALNAME:Maths & Stats: Statistics Seminar
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10864@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20220701T140000Z
DTEND:20220701T150000Z
SUMMARY:Statistics Seminar: COMBSS: Best Subset Selection via Continuous Optimization - Samuel Muller (Macquarie University)
DESCRIPTION:Abstract: Recent rapid developments in information technology have enabled the collection of high-dimensional complex data\, including in engineering\, economics\, finance\, biology\, and health sciences. High-dimensional means that the number of features is large and often far higher thanthe number of collected data samples. In many of these applications\, it is...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10864
LOCATION:Zoom
SEQUENCE:11
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10903@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20220707T140000Z
DTEND:20220707T150000Z
SUMMARY:Statistics Seminar: Two applications of the variational form of Bayes theorem - Håvard Rue (KAUST)
DESCRIPTION:Abstract: In this talk I will discuss the variational form of Bayes theorem by Zellner (1988). This result gives a rationale for the variational (approximate) inference scheme\, which is not always that clear in modern presentations. I will discuss two applications of this results. First\, I will show how to do...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10903
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10869@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20220916T140000Z
DTEND:20220916T150000Z
SUMMARY:Statistics Seminar: Structured prior distributions for the covariance matrix in latent factor models - Sarah Heaps (Durham University)
DESCRIPTION:Abstract: Factor models are widely used for dimension reduction in the analysis of multivariate data. This is achieved through decomposition of a p x p covariance matrix into the sum of two components. Through a latent factor representation\, they can be interpreted as a diagonal matrix of idiosyncratic variances and a...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10869
LOCATION:Boyd Orr 420
SEQUENCE:6
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10908@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20220930T140000Z
DTEND:20220930T150000Z
SUMMARY:Statistics Seminar: Towards intelligent operation and maintenance in large-scale sustainable energy systems - Yingying Zhao (Fudan University )
DESCRIPTION:Abstract: Sustainable energy\, as an alternative to fuel energy\, has readily received concerns from society because of its merits of zero carbon emissions. Owing to the availability of sensor data\, operation and maintenance (O&M) of sustainable energy systems now becomes more intelligent. In particular\, data-driven anomaly detection approaches have gained growing...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10908
LOCATION:Zoom
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10924@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20221007T140000Z
DTEND:20221007T150000Z
SUMMARY:Statistics Seminar: Advanced Bayesian regression and dynamic network modelling - Abdul Salam (University of Groningen\, Netherlands)
DESCRIPTION:Abstract: The talk focuses on two well-known and widely applied statistical model classes\, namely\, the class of dynamic Bayesian network (DBN) models and the class of seemingly unrelated regression (SUR) models. For both model classes we have proposed methodological improvements and we have shown that the improvements can yield significantly better...\N\NNotes: Join Zoom Meetinghttps://uofglasgow.zoom.us/j/89895450683?pwd=N0xDejBocWVQenpnQ2hwQWE4YThOdz09 Meeting ID: 898 9545 0683Passcode: 874624\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10924
LOCATION:Zoom
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10907@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20221014T120000Z
DTEND:20221014T130000Z
SUMMARY:Statistics Seminar: Helping biomedical scientists read the vast research literature using machine learning and natural language processing - Jake Lever (University of Glasgow)
DESCRIPTION:Abstract: Biomedical researchers face an overwhelming number of papers to read as their research becomes increasingly interdisciplinary. We must build automated methods to help them digest this vast knowledge and guide them to new research directions. Information extraction methods offer the opportunity to intelligently summarize the combined biomedical knowledge locked in...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10907
LOCATION:Maths 311B and Zoom
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10913@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20221114T130000Z
DTEND:20221114T140000Z
SUMMARY:Statistics Seminar: Understanding building energy efficiency and tree preservation order by using administrative/emerging urban big data and deep learning - Qunshan Zhao (University of Glasgow)
DESCRIPTION:Abstract: Nowadays\, digital footprints data (geospatial data\, commercial and transactional data\, sensor and image data) have been widely generated and produced in our daily life. However\, how to effectively use these new forms of urban big data has remained unclear and needs further exploration. In this presentation I will introduce two pieces...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10913
LOCATION:Maths 311B
SEQUENCE:6
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10966@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20221118T150000Z
DTEND:20221118T160000Z
SUMMARY:Statistics Seminar: A first approach to Fuzzy Multi-Objective Shortest Path Problems - Irene Marinas (University of Oviedo\, Spain)
DESCRIPTION:Abstract: One of the most studied classical optimization problems is the shortest path problem (SPP). The value of paths is normally measured in terms of a single attribute (cost\, duration\, time\, risk...) defined in each arc of the graph. However\, in many cases\, a single attribute is insufficient to...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10966
LOCATION:Maths 116
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10949@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20221202T130000Z
DTEND:20221202T140000Z
SUMMARY:Statistics Seminar: Big weather\, small health (data) -- statistical models for understanding climate effects on mortality - Theo Economou (The Cyprus Institute)
DESCRIPTION:Abstract: Quantifying the effects of climate change on human health requires weather data as well as public health data. Arguably however\, there are more (publicly available) weather data than health data\, for various reasons but mostly due to the variability in how different countries manage their health data. Having too much...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10949
LOCATION:Maths 311B
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10909@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20221209T150000Z
DTEND:20221209T160000Z
SUMMARY:Statistics Seminar: Generative Quantile Regression with Variability Penalty - Ray Bai (University of South Carolina)
DESCRIPTION:Abstract: Quantile regression and conditional density estimation can often reveal structure that is missed by mean regression\, such as heterogeneous subpopulations (i.e. multimodality) and skewness. In this talk\, we introduce a deep learning generative model for simultaneous quantile regression called Penalized Generative Quantile Regression (PGQR). Our approach simultaneously generates samples from...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10909
LOCATION:Zoom
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10945@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230113T150000Z
DTEND:20230113T160000Z
SUMMARY:Statistics Seminar: Prior Dependence in L1-regularized Bayesian Regression - Christopher Hans (Department of Statistics\, Ohio State University)
DESCRIPTION:Abstract: The regularization of regression coefficients has become a central component of research in the statistical sciences due to its importance in applied data analysis in many other fields of science. From a Bayesian perspective\, regularization is imposed...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10945
LOCATION:Zoom
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10912@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230120T150000Z
DTEND:20230120T160000Z
SUMMARY:Statistics Seminar: Estimating the limiting shape of bivariate scaled sample clouds for self-consistent inference of extremal dependence properties - Emma Simpson (University College London)
DESCRIPTION:Abstract: An integral part of carrying out statistical analysis for bivariate extreme events is characterising the tail dependence relationship between the two variables. For instance\, we may be interested in identifying the presence of asymptotic dependence and/or in determining whether an individual variable can be large while the other is of...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10912
LOCATION:Zoom
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11014@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230201T140000Z
DTEND:20230201T150000Z
SUMMARY:Applied Mathematics\, SofTMech\, Statistics Seminar: Inference in cardiac mechanics - Dirk Husmeier (University of Glasgow)
DESCRIPTION:Abstract: I will be giving a brief overview of the work on inference in cardiac mechanics at SofTMech\, including the following topics: - Simulation versus emulation of cardiac mechanics- Forward versus inverse uncertainty quantification- Structural versus practical identifiability- Dimension reduction of the left...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11014
LOCATION:CTT BOYD ORR:709AB
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10948@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230217T150000Z
DTEND:20230217T160000Z
SUMMARY:Statistics Seminar: Distilling importance sampling for likelihood-free inference - Dennis Prangle (University of Bristol)
DESCRIPTION:Abstract: Likelihood-free inference involves inferring parameter values given observed data and a simulator model. The simulator is computer code taking the parameters\, performing stochastic calculations\, and outputting simulated data. In this work\, we view the simulator as a function whose inputs are (1) the parameters and (2) a vector of pseudo-random...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10948
LOCATION:Zoom
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11031@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230310T150000Z
DTEND:20230310T160000Z
SUMMARY:Statistics Seminar: Transferable species distribution modelling: Comparative performance evaluation and interpretation of novel Generalized Functional Response models - Shaykhah Aldossari (University of Glasgow)
DESCRIPTION:Abstract: Predictive species distribution models (SDMs) are becoming increasingly important in ecology\, in the light of rapid environmental change. The predictions of most current SDMs are specific to the habitat composition of the environments in which such models were fitted. However\, species respond...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11031
LOCATION:Boyd Orr 709A
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11036@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230320T130000Z
DTEND:20230320T140000Z
SUMMARY:Statistics Seminar: A useful parametric specification to model epidemiological data - Marco Mingione (Roma Tre University)
DESCRIPTION:Abstract: Recent epidemic outbreaks reignited the debate on how to properly model epidemiological indicators in order to (i) gain insights into the dynamics of infectious diseases\, (ii) generate epidemic forecasts and (iii) implement timely prevention policies. We argue that the five-parameter specification of the Richards' curve\, often used in the context of...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11036
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10925@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230324T150000Z
DTEND:20230324T160000Z
SUMMARY:Statistics Seminar: Binscatter and adaptive decision tree - Matias D. Cattaneo (Princeton University\, USA)
DESCRIPTION:Abstract: Part 1 Binned scatter plots\, or binscatters\, have become a popular and convenient tool in applied microeconomics for visualizing bivariate relations and conducting informal specification testing. However\, a binscatter\, on its own\, is very limited in what it can characterize about the conditional mean. We introduce a suite of formal...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10925
LOCATION:JOSEPH BLACK:C407 AGRICULT
SEQUENCE:5
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11013@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230421T140000Z
DTEND:20230421T150000Z
SUMMARY:Statistics Seminar: Regression markets and energy forecasting applications - Pierre Pinson (Imperial College London)
DESCRIPTION:Abstract: The operation of energy systems heavily relies on data\, where most agents would benefit from also accommodating data (or more generally information) for other agents. There does not exist\, however\, a general framework that would allow incentivizing information sharing\, with the general objective of improving energy system operation in a...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11013
LOCATION:Maths 311B
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_10960@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230425T120000Z
DTEND:20230425T130000Z
SUMMARY:Statistics Seminar: BioSS Showcase - Peatland Plants and Crop Variety Trials - Mark Brewer\, Claire Harris and Tess Vernon (BioSS)
DESCRIPTION:Abstract: What is BioSS? Mark will briefly answer this question before giving way to two colleagues who will talk about their recent work\, using advanced statistical and biomathematical method to solve important biological and environmental problems. Claire Harris - Modelling peatland plant life Peatlands are hugely important ecosystems in the UK\,...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=10960
LOCATION:Maths 311B
SEQUENCE:5
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11015@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230505T140000Z
DTEND:20230505T150000Z
SUMMARY:Statistics Seminar: Assessing the empirical relationship between agriculture\, manure and ammonia in the Po Valley\, Italy - Paolo Maranzano (University of Milano Bicocca)
DESCRIPTION:Abstract: Ammonia () is a crucial contributor to air pollution levels\, as it can become particulate matter after combining with other pollutant materials from various sources. Around 75% of European ammonia emissions come from livestock production. Emissions occur at all stages of...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11015
LOCATION:Maths 311B
SEQUENCE:4
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11049@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230530T120000Z
DTEND:20230530T130000Z
SUMMARY:Statistics Seminar: There is No Free Variable Importance: Statistical Issues in Explainable Machine Learning - Giles Hooker (Cornell University)
DESCRIPTION:Abstract: The field of machine learning — loosely defined as nonparametric statistical modeling — has become enormously successful over the past fifty years\, partly by forgoing the parametric models familiar to statisticians. A consequence of this philosophy has been that these methods result in algebraically-complex models that...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11049
LOCATION:Maths 311B/Zoom
SEQUENCE:5
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11054@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230616T140000Z
DTEND:20230616T150000Z
SUMMARY:Statistics Seminar: Copula-based approaches for analyzing non-Gaussian spatial data - Huixia Judy Wang (George Washington University)
DESCRIPTION:Abstract: Many existing methods for analyzing spatial data rely on the Gaussian assumption\, which is violated in many applications such as wind speed\, precipitation and COVID mortality data. In this talk\, I will discuss several semiparametric approaches for analyzing non-Gaussian spatial data through copula modeling. I will first present a copula-based...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11054
LOCATION:Maths 311B/Zoom
SEQUENCE:3
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
BEGIN:VEVENT
UID:GLW_UNI_MS_WEBEVT_11040@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20230901T140000Z
DTEND:20230901T150000Z
SUMMARY:Statistics Seminar: TBA - Raphael Huser (KAUST)
DESCRIPTION:More information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11040
LOCATION:Maths 311B
SEQUENCE:2
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
END:VCALENDAR