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55:22 Ivan Oseledets 11 January 2021 Machine learning… Ivan Oseledets 11 January 2021 Machine learning and numerical methods	Ivan Oseledets 11 January 2021 Machine learning and numerical methods An automated programme has been used to generate the subtitles on this talk. icms owna function parameters optimization lot functions approximation basis problem model network idea samples linear method networks gradient image class output solution From ALASDAIR SPRATT on January 11th, 2021 0 likes 39 plays 0 Course Code ICMS Publisher ICMS Licence Type All rights reserved Language English Date Created January 11th, 2021
49:18 NLU+ Lecture 5: Feed Forward Neural Networks NLU+ Lecture 5: Feed Forward Neural Networks	NLU+ Lecture 5: Feed Forward Neural Networks Feed Forward Neural Networks informatics nlu vector function model probability thing lot output word perceptron distribution things network words models bunch input parameters language regression matrix From Ruairi O'Hare on December 29th, 2020 0 likes 4 plays 0 Licence Type All rights reserved The University of Edinburgh Language English Date Created December 29th, 2020
18:17 REF2020: Daniel Adamiak- Small-x Helicity… REF2020: Daniel Adamiak- Small-x Helicity Phenomenology	REF2020: Daniel Adamiak- Small-x Helicity Phenomenology REF2020: Daniel Adamiak- Small-x Helicity Phenomenology higgs centre ref2020 theory proton distribution quarks spin amplitude parameters helicity pdfs distributions momentum minus band uncertainties functions contribution bands electron x. function From Lyndsey Ballantyne on December 18th, 2020 0 likes 0 plays 0 Licence Type All rights reserved The University of Edinburgh Date Created December 9th, 2020
15:22 NLU+ Lecture 3: Conditional Language Modelling… NLU+ Lecture 3: Conditional Language Modelling with n-grams (2019 version)	NLU+ Lecture 3: Conditional Language Modelling with n-grams (2019 version) Machine Translation Model informatics nlu model word parameters translation words alignment sentence algorithm probability things counts variable thing models question lot likelihood stuff language problem From Ruairi O'Hare on December 17th, 2020 0 likes 5 plays 0 Licence Type All rights reserved The University of Edinburgh Language English Date Created December 17th, 2020
24:25 REF2020: Ignazio Scimemi- Uncertainties and… REF2020: Ignazio Scimemi- Uncertainties and challenges in TMD extraction	REF2020: Ignazio Scimemi- Uncertainties and challenges in TMD extraction REF2020: Ignazio Scimemi- Uncertainties and challenges in TMD extraction higgs centre ref2020 pdf tmd tmds evolution energy boson prescription scale situation lhc question sets canada values cross uncertainty difference region correlation parameters From Lyndsey Ballantyne on December 11th, 2020 0 likes 5 plays 0 Licence Type All rights reserved The University of Edinburgh Date Created December 7th, 2020
47:57 Ruth King (University of Edinburgh) Title: To… Ruth King (University of Edinburgh) Title: To integrated models ... and beyond …	Ruth King (University of Edinburgh) Title: To integrated models ... and beyond … Friday 4 December Ruth King (University of Edinburgh)Title: To integrated models ... and beyond …Abstract: Capture-recapture studies are often conducted on wildlife populations in order to… statistics research capture probability animal survival model probabilities animals process matrix history likelihood recovery observation parameters age colony thing models availability breeding From OLLIE Quinn on December 7th, 2020 0 likes 10 plays 0 Licence Type All rights reserved Language English Date Created December 4th, 2020
01:37:35 MLP Advanced NN Tutorial 05 - Transformers;… MLP Advanced NN Tutorial 05 - Transformers; Meta-Learning	MLP Advanced NN Tutorial 05 - Transformers; Meta-Learning Machine Learning Practical advanced tutorial (optional) - Session 5 (Week 11). machine learning deep learning transformers meta-learning learner training learning thing model loop things network test tasks process meta task attention gradients respect loss parameters generalisation layer From Pavlos Andreadis on December 5th, 2020 1 likes 17 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
06:35 MLP Lecture 07 - Clip 06 - Multiple Feature Maps MLP Lecture 07 - Clip 06 - Multiple Feature Maps	MLP Lecture 07 - Clip 06 - Multiple Feature Maps Machine Learning Practical (MLP) Lecture 07, Clip 06 / 09. machine learning deep learning times feature maps channels input image kernel size units kernels channel output matrices parameters 3-dimensions dimension dimensionality connections bias capital From Pavlos Andreadis on November 2nd, 2020 1 likes 182 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
07:58 Medical Sciences 1: Pharmacokinetic Aspects of… Medical Sciences 1: Pharmacokinetic Aspects of General Anaesthesia Part 4 Dr Phil Larkman	Medical Sciences 1: Pharmacokinetic Aspects of General Anaesthesia Part 4 Dr Phil Larkman Physiological influences on anaesthetic distribution brain drug anesthetic blood plasma anesthesia solubility concentration levels protein anesthetics parameters ketamine output drugs proteins rate induction effects agents From Philip Larkman on October 19th, 2020 0 likes 57 plays 0 Licence Type Creative Commons - Attribution
45:15 Research and teaching in statistical and data… Research and teaching in statistical and data sciences seminars: Daniela Castro-Camilo	Research and teaching in statistical and data sciences seminars: Daniela Castro-Camilo Daniela Castro Camilo (University of Glasgow)Title: Bayesian space-time gap filling for inference on extreme hot-spots: an application to Red Sea surface temperaturesAbstract: We develop a method for… statistics research data science model dependence distribution anomalies structure space approach values threshold models bit points gaps independence scale neighborhood location stationarity parameters temperature From OLLIE Quinn on October 14th, 2020 0 likes 25 plays 0 Licence Type All rights reserved Language English Date Created October 9th, 2020
12:25 MLP Lecture 04 - Clip 03 - Data splits MLP Lecture 04 - Clip 03 - Data splits	MLP Lecture 04 - Clip 03 - Data splits Machine Learning Practical (MLP) Lecture 04, Clip 03 / 05. machine learning deep learning test validation training network model error performance networks lots cross hyperparameters decisions parameters generalization times kind models capacity exam proxy From Pavlos Andreadis on October 11th, 2020 1 likes 213 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
09:20 MLP Lecture 04 - Clip 02 - Generalisation MLP Lecture 04 - Clip 02 - Generalisation	MLP Lecture 04 - Clip 02 - Generalisation Machine Learning Practical (MLP) Lecture 04, Clip 02 / 05. machine learning deep learning network training test model validation error performance sets hyperparameters samples thing testing weights capacity proxy functions activation parameters networks kind From Pavlos Andreadis on October 11th, 2020 1 likes 220 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
44:18 IMA, LMS Joint Meeting: Topological methods in… IMA, LMS Joint Meeting: Topological methods in Data Science (1-2 October 2020)	IMA, LMS Joint Meeting: Topological methods in Data Science (1-2 October 2020) An automated programme is used to generate the subtitles on this talk. You can remove the subtitles by pressing CC on the bottom toolbar. Ran Levi (Aberdeen) - Combinatorial Structures in Neural… graph coefficient parameters vertices thing tournaments things tribes parameter complex neurons vertex brain respect matrix density neighborhood tournament clicks edges From Liam Holligan on October 9th, 2020 0 likes 23 plays 0 Licence Type All rights reserved Language English Date Created October 1st, 2020
48:50 Research and the “AI Revolution” \|… Research and the “AI Revolution” \| Professor Christopher Bishop \| Distinguished Lecture \| School of Informatics	Research and the “AI Revolution” \| Professor Christopher Bishop \| Distinguished Lecture \| School of Informatics Recording of Research and the “AI Revolution” - a School of Informatics Distinguished Lecture presented by Professor Christopher Bishop on 5 October 2020. Christopher Bishop is a… school of informatics artificial intelligence professor christopher bishop distinguished lecture ai revolution the university of edinburgh microsoft machine learning sort expertise molecules things ai application networks technologies examples storage algorithms process bit idea domain space parameters From Nicola Hopper on October 6th, 2020 0 likes 91 plays 0 Publisher UoE School of Informatics Licence Type All rights reserved The University of Edinburgh Language English Date Created October 5th, 2020
17:15 Lecture 9 - Fundamentals of Optimisation Lecture 9 - Fundamentals of Optimisation	Lecture 9 - Fundamentals of Optimisation Lecture 9 - Fundamentals of Optimisation heat transfer flow function optimization rate integer exchanger efficiency fluid coefficient input column variables parameters mass variable sequence engineering chemical From Mennatallah Mohamed Awny Ali Labib on September 29th, 2020 0 likes 68 plays 0 Course Code CHEEE1005 - CHEDSE4 Licence Type All rights reserved The University of Edinburgh Language English

Search for tag: "parameters"

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