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AI3SD Video: Dimensionality in chemistry: using multidimensional data for machine learning

AI3SD Video: Dimensionality in chemistry: using multidimensional data for machine learning
AI3SD Video: Dimensionality in chemistry: using multidimensional data for machine learning
In the last hundred years mankind has fully absorbed the idea of multi-dimensional space, starting with 4D space time. Due to the increase in computational power, scientists can now manipulate molecules in 4D (3D vibrating molecules in VR) and work with multidimensional datasets, which are needed to utilize big data and machine learning. However, our intuition from 3D space can fall down when dealing with higher dimensions and a lack of intuition can lead to mistakes in analysis. In this talk I will discuss how to think about the best dimensional space to use to describe chemical problems, how multi-dimensional space is different, techniques for using it and analysing the outputs of machine learning.
AI, AI3SD Event, Artificial Intelligence, Chemistry, Machine Intelligence, Machine Learning, ML, Molecules, multidimensional data
Gale, Ella
24d979c7-f91f-4ccd-979c-56dcbf99acf1
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Gale, Ella
24d979c7-f91f-4ccd-979c-56dcbf99acf1
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Gale, Ella (2020) AI3SD Video: Dimensionality in chemistry: using multidimensional data for machine learning. Kanza, Samantha, Frey, Jeremy G., Niranjan, Mahesan and Hooper, Victoria (eds.) AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom. 01 Jul - 23 Sep 2020. (doi:10.5258/SOTON/P0050).

Record type: Conference or Workshop Item (Other)

Abstract

In the last hundred years mankind has fully absorbed the idea of multi-dimensional space, starting with 4D space time. Due to the increase in computational power, scientists can now manipulate molecules in 4D (3D vibrating molecules in VR) and work with multidimensional datasets, which are needed to utilize big data and machine learning. However, our intuition from 3D space can fall down when dealing with higher dimensions and a lack of intuition can lead to mistakes in analysis. In this talk I will discuss how to think about the best dimensional space to use to describe chemical problems, how multi-dimensional space is different, techniques for using it and analysing the outputs of machine learning.

Video
AI3SDOnlineSeminarSeries-5-EG-050820 - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 5 August 2020
Additional Information: Dr. Ella M Gale is the machine learning subject specialist attached to the Technology Enhanced Chemical Synthesis Centre for Doctoral Training at the University of Bristol. She has a PhD in Computational Chemistry from Imperial College London. In her career since she has worked in a set of diverse areas: neural networks, AI, cellular automata, unconventional computing, machine learning, memristors, computer vision, nanotechnology, materials science and supports colleagues in chemical engineering and synthetic chemistry. Her current research interests are applying machine learning techniques to de novo drug design and retrosynthesis and applying computer vision techniques to chemistry lab monitoring.
Venue - Dates: AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom, 2020-07-01 - 2020-09-23
Keywords: AI, AI3SD Event, Artificial Intelligence, Chemistry, Machine Intelligence, Machine Learning, ML, Molecules, multidimensional data

Identifiers

Local EPrints ID: 447294
URI: http://eprints.soton.ac.uk/id/eprint/447294
PURE UUID: 3e171abd-3f41-453b-b26a-36a54d4bab07
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302

Catalogue record

Date deposited: 08 Mar 2021 17:35
Last modified: 09 Mar 2021 02:54

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Contributors

Author: Ella Gale
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Mahesan Niranjan
Editor: Victoria Hooper

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