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39:47 GAGTA 14 Markus Lohrey GAGTA 14 Markus Lohrey	GAGTA 14 Markus Lohrey 7-11 June 2021, GAGTA 14 2021 Markus Lohrey Groups with hard compressed word problems This recording is in the process of being subtitled. Subtitles will be available in due course. icms gagta lohrey theory method solution data analysis groups hard compressed word problems problem space complexity sense input gates circuit class result algorithm programme bit log gate compress quotient length From Anna Munro on June 16th, 2021 0 likes 2 plays 0 Licence Type All rights reserved Language English Date Created June 9th, 2021
03:02 Pim van der Hoorn EVA Talk Preview Pim van der Hoorn EVA Talk Preview	Pim van der Hoorn EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Pim van der Hoorn Talk Title: Tails in networks: a tale of finding the right slope. Abstract: Network… theory solution model eva icms tail tale slope networks science data nodes degrees function distribution measures performance integer network talk authors k. degree triangles behaviour types estimators regularity conjecture question log From Anna Munro on May 24th, 2021 0 likes 5 plays 0 Licence Type All rights reserved Language English
03:28 Johannes Buck EVA Talk Preview Johannes Buck EVA Talk Preview	Johannes Buck EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Johannes Buck Talk Title: Properties and Consistency of QTree in Max-Linear Models Under Observational Noise… icms eva solution theory model properties consistency max-linear noise river networks tree equation distribution edge linear minimum score max edges log lock assumptions gap algorithm bit estimator outputs theorem From Anna Munro on May 24th, 2021 0 likes 8 plays 0 Licence Type All rights reserved Language English
03:29 Rafail Kartsioukas EVA Talk Preview Rafail Kartsioukas EVA Talk Preview	Rafail Kartsioukas EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Rafail Kartsioukas Talk Title: On the rate of concentration of maxima in Gaussian arrays Abstract: It has… solution theory icms eva arrays assumptions classics conditions epsilon log property tau bound bounds concentration rate models transformations examples transition probability subsets sequence gate class stove phenomenon From Anna Munro on May 19th, 2021 0 likes 5 plays 0 Licence Type All rights reserved Language English
03:36 Michael Allouche EVA Talk Preview Michael Allouche EVA Talk Preview	Michael Allouche EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Michael Allouche Talk Title: On the approximation of extreme quantiles with ReLU neural networks Abstract:… eva icms allouche theory solution neural networks networks quantiles relu linear units linear functions gan function log minus network alpha illustration approximation tail rate sigma error regularity phi theorem training model generative talk From Anna Munro on May 13th, 2021 0 likes 13 plays 0 Licence Type All rights reserved Language English
21:09 Soft matter quasicrystals with six-fold symmetry:… Soft matter quasicrystals with six-fold symmetry: pattern formation, mode interactions and tilings - Andrew Archer	Soft matter quasicrystals with six-fold symmetry: pattern formation, mode interactions and tilings - Andrew Archer New directions in classical density functional theory online workshop 3 - 6 May 2021 Andrew Archer (University of Loughborough) Soft matter quasicrystals with six-fold symmetry: pattern formation,… mathematics tiling profile density thing structure crystal vectors length triangles tiles formation minimum circles quasar pattern log ratio space kinds interactions From GILLIAN KERR on May 6th, 2021 0 likes 8 plays 0 Licence Type All rights reserved Language english Date Created May 6th, 2021
48:14 BMC BAMC 2021 Colva M. Roney-Dougal BMC BAMC 2021 Colva M. Roney-Dougal	BMC BAMC 2021 Colva M. Roney-Dougal 6-9 April 2021, BMC BAMC 2021 This talk was a BMC morning lecture by Colva M. Roney-Dougal (University of Saint Andrews) Titled: Finite Simple Groups and Computational Complexity This recording is… bmc bamc 2021 roney-dougal icms maths mathematics math computational complexity finite simple groups points problem base size subgroup permutation isomorphism things alpha point groups subsets element permutations omega elements thing log bit string From Sophia Martin on April 27th, 2021 0 likes 25 plays 0 Licence Type All rights reserved Language English Date Created April 6th, 2021
27:31 EEA 2021 - Linear Regression EEA 2021 - Linear Regression	EEA 2021 - Linear Regression Lecture for linear regression and non-parametric equivalent. linear regression model variable correlation analysis relationship variables variance residuals heteroscedasticity bit models assumption variation values assumptions log test x. From Kyle Dexter on March 4th, 2021 0 likes 74 plays 0 Licence Type Creative Commons - Attribution Non Commercial
33:20 Statistics in COVID-19: Simon Wood (School of… Statistics in COVID-19: Simon Wood (School of Mathematics, University of Edinburgh)	Statistics in COVID-19: Simon Wood (School of Mathematics, University of Edinburgh) Simon Wood (School of Mathematics, University of Edinburgh): Does the data know it should follow the science? When was R<1 and incidence in decline? The CfS Research Day gathered together experts… statistics covid-19 model infection lockdown thing bit hospital function likelihood infections distribution death incidence assumption lock deaths incidents log analysis smoothness things From Belle Taylor on March 1st, 2021 0 likes 14 plays 0 Publisher Centre for Statistics Licence Type All rights reserved Language English Date Created March 1st, 2021
56:44 Sara Wade & Karla Monterrubio-Gomez… Sara Wade & Karla Monterrubio-Gomez (Edinburgh): On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach.	Sara Wade & Karla Monterrubio-Gomez (Edinburgh): On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach. The subtitles/captions on this talk are being edited. They will be available within 2 weeks of the talk being published. 26 February 2021Sara Wade & Karla Monterrubio-Gomez (Edinburgh): On MCMC… statistics research function likelihood estimator scheme points covariance parameters process approximation hyperparameters matrix poisson block point quadrature log locations framework approach pseudo From OLLIE Quinn on March 1st, 2021 0 likes 20 plays 0 Licence Type All rights reserved Language English Date Created March 26th, 2021
06:05 Resistivity_Master_Curve_Matching Resistivity_Master_Curve_Matching	Resistivity_Master_Curve_Matching Description of how to do curve matching to a set of master curves used in 1-D resistivity surveying geophysics geosciences master log curve resistivity paper axis electrode curves layer values decades resistivities graph separation plot fit tracing scale instruction kappa From Wyn Williams on February 27th, 2021 0 likes 73 plays 0 Course Code EASC08008 Licence Type All rights reserved The University of Edinburgh Language English Date Created February 27th, 2021
47:46 ASR Lecture 9 part I ASR Lecture 9 part I	ASR Lecture 9 part I ASR Lecture 9: WFSTs for ASR (partial lecture due to technical issues) speech recognition transducer probability bit output symbol weights probabilities point composition word path log input sequence weight pizza outputs grandma recognition loop From Peter Bell on February 15th, 2021 0 likes 107 plays 0 Licence Type Creative Commons - Attribution Non Commercial Date Created February 8th, 2021
18:31 FDS-S2-02-2-5 Maximum likelihood estimation of… FDS-S2-02-2-5 Maximum likelihood estimation of logistic regression coefficients	FDS-S2-02-2-5 Maximum likelihood estimation of logistic regression coefficients We introduce the principle of maximum likelihood, and show how to derive the likelihood as a function of the coefficients for logistic regression. We also mention one topical application of logistic… inf2-fds beta log likelihood probability regression term failure function i. success sum naught principle coefficients point respect x. dataset equals thing From David Sterratt on January 20th, 2021 0 likes 158 plays 0 Course Code INFR08030 Publisher David Sterratt Licence Type Creative Commons - Attribution Non Commercial No Derivatives Language English Date Created January 20th, 2021
11:17 FDS-S2-02-2-4 The logistic regression classifier FDS-S2-02-2-4 The logistic regression classifier	FDS-S2-02-2-4 The logistic regression classifier We show how to make a logistic regression classifier, and, in the context of ethics, consider how transparent logistic regression can be made to people whose lives it affects. We also compare… inf2-fds regression log boundary probability credit decision classifier neighbours odds neighbour income ratio variables algorithm score customers approval beta linear age From David Sterratt on January 20th, 2021 0 likes 162 plays 0 Course Code INFR08030 Publisher David Sterratt Licence Type Creative Commons - Attribution Non Commercial No Derivatives Language English Date Created January 20th, 2021
10:14 FDS-S2-02-2-3 Multiple logistic regression and… FDS-S2-02-2-3 Multiple logistic regression and confidence and intervals	FDS-S2-02-2-3 Multiple logistic regression and confidence and intervals We extend logistic regression to multiple independent variables, and show how we can use the boostrap to estimate confidence intervals for coefficients, and to test hypotheses. inf2-fds odds beta regression hypothesis bootstrap intervals age confidence ratio hat method log credit coefficients coefficient variables fact statistic 95th dataset From David Sterratt on January 20th, 2021 0 likes 177 plays 0 Course Code INFR08030 Publisher David Sterratt Licence Type Creative Commons - Attribution Non Commercial No Derivatives Language English Date Created January 20th, 2021
25:56 Distillation Lecture 5 2020 part 3 Distillation Lecture 5 2020 part 3	Distillation Lecture 5 2020 part 3 Distillation Lecture 5 2020 Activity coefficients: derivation from Gibbs free energy times term activity equation coefficients expression log minus parameter a1 moles values lot gibbs energy respect n1 fact form suffix From John Christy on December 31st, 2020 0 likes 48 plays 0 Course Code CHEE11023 Publisher John Christy Licence Type All rights reserved The University of Edinburgh Language English (British) Date Created December 31st, 2020

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