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sustainable handout.dvi
www.tcm.phy.cam.ac.uk/~jsb56/resources/sustainablehandout.pdf24 Oct 2022: This is where air-conditioningcomes in. In fact the economics of cooling are pretty similar to heating, hot countries mightbe 30-40C, so we again want 10-20C of temperature change. ... In fig. 17 you see a map ofthe UK with the only real economic Results that match 1 of 2 words
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Intellegens_Apr22
www.tcm.phy.cam.ac.uk/~tmw38/Whitehead22.pdf21 Nov 2022: These output properties consisted of eight sets of tests, with each test run at both a high (approx. ... Fig. 1. The coefficient of determination in prediction of each output property against the holdout test set, showing predictions of both high and low -
Alchemite™ machine learning
www.tcm.phy.cam.ac.uk/~gjc29/talks/AnsysTalk2022.pdf3 Mar 2022: You are combining data from different sources or projects. Projects with different goals test different properties. ... Noisy due to variability of machines / labs / operators. You cannot test every build for every property. -
Electronic structure discussion group
www.tcm.phy.cam.ac.uk/events/esdg.html6 Apr 2022: talk made reference to the following reports: The economic impact of molecular modelling and Industry interactions of the electronic structure research community in Europe.). -
Imputation of Sensory Properties Using DeepLearningMatthew Segall ( …
www.tcm.phy.cam.ac.uk/~tmw38/Mahmoud21.pdf21 Nov 2022: and test sets, from an average R2 of 0.41 to 0.30. ... subject to greater inter-individual variability between test subjects. Nonetheless, Alchemite Imputation model. -
Batteries flyer
www.tcm.phy.cam.ac.uk/~gjc29/flyers/Batteries_long_1.pdf15 Oct 2022: Nature publication). Machine Learning for Battery Optimisation(white paper). BATTERIESThe future widespread adoption of electric vehicles will result in reduced harmful emissions andcleaner air, among other social and economic benefits. -
Intellegens_Apr22
www.tcm.phy.cam.ac.uk/~gjc29/papers/WhiteheadChenDalyConduit22.pdf4 Feb 2022: These output properties consisted of eight sets of tests, with each test run at both a high (approx. ... Fig. 1. The coefficient of determination in prediction of each output property against the holdout test set, showing predictions of both high and low -
Machine learning forbattery applications Optimise battery…
www.tcm.phy.cam.ac.uk/~gjc29/flyers/Batteries_2.pdf15 Oct 2022: But battery R&D is complexand slow, with many competing factors to balance, and aheavy reliance on time-consuming, costly experiments to fillgaps in data and test prototypes. -
AI UK 2022 presentation 3
www.tcm.phy.cam.ac.uk/~gjc29/talks/AIUKTalk2022.pdf18 Mar 2022: Optimise battery cells and packs,. reducing the number of tests and prototypes. -
Data-driven design anddevelopment of Materials Design materials,…
www.tcm.phy.cam.ac.uk/~gjc29/flyers/Materials_Industry_1.pdf15 Oct 2022: Because this data comes from diverse sources and tests, ittends to be ‘sparse’, causing problems for conventionalmachine learning.
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