Event Diary
Mon 15 Apr, '24 - Fri 19 Apr, '24All-day |
Frag-coag WorkshopMS.03Runs from Monday, April 15 to Friday, April 19. This workshop is in association with CRiSM and is the fourth of series of earlier events held in 2012, 2015, and 2019. For this edition there will be an additional theme of fragmentation and coalescence, in association with the EPSRC project "Random fragmentation-coalescence processes out of equilibrium". |
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Mon 22 Apr, '24- |
Statistics SeminarMS.03, Zeeman |
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Mon 6 May, '24- |
Statistics SeminarMB0.07, MSB |
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Mon 13 May, '24- |
Statistics SeminarMB0.07, MSB |
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Thu 16 May, '24 |
Interdisciplinary workshop - Quantifying Carbon footprintScarman Space 24TBC |
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Mon 20 May, '24- |
Statistics SeminarMB0.07, MSB |
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Mon 27 May, '24- |
Statistics SeminarMB0.07, MSB |
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Mon 3 Jun, '24- |
Statistics SeminarMB0.07, MSB |
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Wed 5 Jun, '24 - Fri 7 Jun, '2410:00 - 17:00 |
BioInference 2024MS.01Runs from Wednesday, June 05 to Friday, June 07. If you are interested on mathematical modelling and statistical methods for (widely defined/interpreted) biological problems, then save the date for BioInference2024 (5th -7th June, here at Warwick), and consider sending an abstract for a poster/talk. |
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Mon 10 Jun, '24 - Wed 12 Jun, '24All-day |
Workshop on Heterogeneous and Distributed DataMS.01Runs from Monday, June 10 to Wednesday, June 12. The aim of the event is to bring together researchers in areas such as missing data, (local) differential privacy, communication-constrained inference and transfer learning to share recent progress and motivate future directions. |
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Mon 10 Jun, '24- |
Statistics SeminarMB0.07, MSB |
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Mon 17 Jun, '24- |
Statistics SeminarMB0.07, MSB |
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Mon 24 Jun, '24- |
Statistics SeminarMB0.07, MSB |
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Mon 9 Sep, '24 - Tue 10 Sep, '24All-day |
Data Visualisation -Paul Murrell MasterclassRootes Building, Chancellors 1 and 2Runs from Monday, September 09 to Tuesday, September 10. This 2-day course covers the big data visualisation questions: *what* should I draw and *how* should I draw it. Discover how to represent your data visually, following guidelines that play to the strengths of our visual system while avoiding its weaknesses, using the R package ggplot2. |