Search for tag: "convolution"

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43:17 Uwe Franz The discrete Weyl relations and… Uwe Franz The discrete Weyl relations and completely positive maps	Uwe Franz The discrete Weyl relations and completely positive maps Applied matrix positivityUwe Franz The discrete Weyl relations and completely positive maps This recording is in the process of being subtitled. Subtitles will be available in due course. applied matrix positivity basis maps groups matrices linear error character identity times respect star convolution unit properties formula operators representation bases From Greg McCracken 0 likes 13 plays 0 Licence Type All rights reserved Language English Date Created July 20th, 2021
16:05 Spatial Extremes: Anders Rønn-Nielsen Spatial Extremes: Anders Rønn-Nielsen	Spatial Extremes: Anders Rønn-Nielsen This talk has been automatically captioned. You can remove these by pressing CC on the video toolbar. Name: Anders Rønn-Nielsen Talk Title: Extreme value theory for spatial random fields -… eva sets field distribution function condition sequence result measure convolution basis behaviour domain kernel conditions increases convex supremum attraction tail distributions From Belle Taylor 0 likes 35 plays 0 Publisher Centre for Statistics Licence Type All rights reserved Language English Date Created June 29th, 2021
17:07 REF2020: Georgios Billis- QCD+QED qT… REF2020: Georgios Billis- QCD+QED qT Factorization for Z/W production and decay	REF2020: Georgios Billis- QCD+QED qT Factorization for Z/W production and decay REF2020: Georgios Billis- QCD+QED qT Factorization for Z/W production and decay higgs centre ref2020 function factorization boson functions vector side convolution radiation measurement lepton leptons heart delta piece modes momenta regime pieces eft particle From Lyndsey Ballantyne 0 likes 23 plays 0 Licence Type All rights reserved The University of Edinburgh Date Created December 7th, 2020
20:14 Topic 75: Difference Equation Analysis of… Topic 75: Difference Equation Analysis of Input-Output Time-Domain Statistics (PETARS, Chapter 10)	Topic 75: Difference Equation Analysis of Input-Output Time-Domain Statistics (PETARS, Chapter 10) This topic considers extending previous topics on calculating the input-output statistics of a linear time-invariant (LTI) system in response to a wide-sense stationary (WSS) process at the input,… pgee11164 difference input output equation autocorrelation expression equations covariance solution auto alpha minus topic correlation convolution response times impulse statistics process From James Hopgood 0 likes 73 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created November 30th, 2020
32:23 Topic 72: Time-Domain Analysis of Response to… Topic 72: Time-Domain Analysis of Response to Random Signals using the System Impulse Response (PETARS, Chapter 10)	Topic 72: Time-Domain Analysis of Response to Random Signals using the System Impulse Response (PETARS, Chapter 10) This video looks at the method for calculating the output statistics for a linear time-invariant (LTI) system in response to a wide-sense stationary (WSS) input using a time-domain method given the… pgee11164 output input response impulse autocorrelation sequence covariance function convolution cross correlation summation expression minus auto statistics linear decay process result From James Hopgood 0 likes 119 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created November 26th, 2020
02:24 MLP Lecture 08 - Clip 03 - Gradients w.r.t. Inputs MLP Lecture 08 - Clip 03 - Gradients w.r.t. Inputs	MLP Lecture 08 - Clip 03 - Gradients w.r.t. Inputs Machine Learning Practical (MLP) Lecture 08, Clip 03 / 05. machine learning deep learning gradient convolution input kernel layer From Pavlos Andreadis 1 likes 342 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
06:46 MLP Lecture 08 - Clip 02 - Gradients w.r.t.… MLP Lecture 08 - Clip 02 - Gradients w.r.t. Weights	MLP Lecture 08 - Clip 02 - Gradients w.r.t. Weights Machine Learning Practical (MLP) Lecture 08, Clip 02 / 05. machine learning deep learning layer convolution gradient weights From Pavlos Andreadis 1 likes 381 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
04:49 MLP Lecture 08 - Clip 01 - Dilated Convolutions MLP Lecture 08 - Clip 01 - Dilated Convolutions	MLP Lecture 08 - Clip 01 - Dilated Convolutions Machine Learning Practical (MLP) Lecture 08, Clip 01 / 05. machine learning deep learning pixels size kernel unit convolution operation times field layers units layer computations patch thing weights transformations functions end padding pixel From Pavlos Andreadis 1 likes 451 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
55:00 MLP Lecture 08 - Convolutional Neural Networks… MLP Lecture 08 - Convolutional Neural Networks (2) - 2019 temp version	MLP Lecture 08 - Convolutional Neural Networks (2) - 2019 temp version Machine Learning Practical (MLP) Lecture 08, temporary 2019-20 live version. machine learning deep learning convolution layers inputs output gradients kernel weights error From Pavlos Andreadis 1 likes 517 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
53:43 MLP Q&A 2 - Session 3 (Week 7) MLP Q&A 2 - Session 3 (Week 7)	MLP Q&A 2 - Session 3 (Week 7) Machine Learning Practical Q&A 2 - Session 3 (Week 7). machine learning deep learning things image network kernel convolution question output fan From Pavlos Andreadis 1 likes 38 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
02:36 MLP Lecture 07 - Clip 07 - Pooling/Subsampling MLP Lecture 07 - Clip 07 - Pooling/Subsampling	MLP Lecture 07 - Clip 07 - Pooling/Subsampling Machine Learning Practical (MLP) Lecture 07, Clip 07 / 09. machine learning deep learning layer patch image output window convolution input layers features feature fisherman cooling pixels pooling types structure computation memory size convolutions From Pavlos Andreadis 1 likes 449 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
06:22 MLP Lecture 07 - Clip 03 - Example MLP Lecture 07 - Clip 03 - Example	MLP Lecture 07 - Clip 03 - Example Machine Learning Practical (MLP) Lecture 07, Clip 03 / 09. convolution kernel machine learning example From Pavlos Andreadis 2 likes 491 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
03:32 MLP Lecture 07 - Clip 02 - What are Convolutions? MLP Lecture 07 - Clip 02 - What are Convolutions?	MLP Lecture 07 - Clip 02 - What are Convolutions? Machine Learning Practical (MLP) Lecture 07, Clip 02 / 09. convolution kernel machine learning deep learning From Pavlos Andreadis 1 likes 527 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
18:24 Topic 40: Sum of Independent Random Variables… Topic 40: Sum of Independent Random Variables (PETARS, Chapter 5)	Topic 40: Sum of Independent Random Variables (PETARS, Chapter 5) This Topic considers further the sum of random variables that was introduced in Topic 33 on auxiliary variables. The case of independent random variables and vectors is considered specifically,… pgee11164 variables sum probability function pdf convolution functions result mass expectation times l. summation respect overlap inverse variable density sense k. From James Hopgood 0 likes 217 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created October 16th, 2020
31:53 Locally analytic representations of p-adic groups… Locally analytic representations of p-adic groups talk 2 - Nicolas Dupre	Locally analytic representations of p-adic groups talk 2 - Nicolas Dupre LMS Autumn Algebra school Locally analytic representations of p-adic groups - talk 2 Nicolas Dupre 6 October 2020 An automated programme is used to generate the subtitles on this talk. You can… algebra kind thing distribution topology representations things functions space distributions elements vector tensor multiplication fact field spaces convolution convex k. From GILLIAN KERR 0 likes 31 plays 0 Licence Type All rights reserved Language english Date Created October 6th, 2020
50:39 S Gunningham S Gunningham	S Gunningham Sam Gunningham: The Springer correspondence algebra semi representations space dimension fibers spring category object components convolution picture sort homology bit fact basis thing steinberg fiber From Greg McCracken 0 likes 21 plays 0 Licence Type All rights reserved Language English Date Created September 25th, 2020

Search for tag: "convolution"

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