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Powering innovation in artificial intelligence with Open Access research...

Artificial intelligence (AI) and machine learning (ML) together represent a research frontier with a wide variety of discipline specific applications. At Strathclyde researchers in Computer & Information Sciences are exploring improved AI planning models to enable improved decision making by automous agents. Meanwhile, research conducted by the Aerospace Centre of Excellence is using AI and computational techniques to optimize the efficacy of certain astronautic applications. This includes 'global trajectory optimization' to aircraft and spacecraft design, from the planning and scheduling for autonomous vehicles to the synthesis of robust controllers for airplanes or satellites.

AI is also transforming the research agenda within Finance, where researchers are exploring the potential of AI and machine learning in evaluating banking risks and in new, emerging aspects of FinTech.

Explore some of this Open Access research from Computer & Information Sciences, Aerospace Centre of Excellence and Finance. Or explore all of Strathclyde's Open Access research...

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Number of items: 16.

Higham, Catherine F. and Higham, Desmond J. (2019) Deep learning : an introduction for applied mathematicians. SIAM Review, 61 (4). 860–891. ISSN 0036-1445

Estrada, Ernesto and Hatano, Naomichi (2016) Communicability angle and the spatial efficiency of networks. SIAM Review, 58 (4). pp. 692-715. ISSN 0036-1445

Pestana, Jennifer and Wathen, Andrew J. (2015) Natural preconditioning and iterative methods for saddle point systems. SIAM Review, 57 (1). 71–91. ISSN 0036-1445

Elman, H.C. and Ramage, Alison and Silvester, D.J. (2014) IFISS : a computational laboratory for investigating incompressible flow problems. SIAM Review, 56 (2). pp. 261-273. ISSN 0036-1445

Grindrod, P. and Higham, D.J. (2013) A matrix iteration for dynamic network summaries. SIAM Review, 55 (1). pp. 118-128. ISSN 0036-1445

Estrada, Ernesto and Higham, Desmond (2010) Network properties revealed through matrix functions. SIAM Review, 52 (4). pp. 696-714.

Higham, Desmond J. (2008) Modeling and simulating chemical reactions. SIAM Review, 50 (2). pp. 347-368. ISSN 0036-1445

Higham, Desmond J. (2007) A matrix perturbation view of the small world phenomenon. SIAM Review, 49 (1). pp. 91-108. ISSN 0036-1445

Higham, D.J. (2007) A matrix perturbation view of the small world phenomenon, SIAM Review SIGEST section. SIAM Review, 49 (1). pp. 91-108. ISSN 0036-1445

McBride, A.C. (2005) BIG is Beautiful. SIAM Review, 34. pp. 26-32. ISSN 0036-1445

Ainsworth, M. (2004) Review of Adaptive Finite Element Methods for Differential Equations by W Bangerth and R Rannacher. SIAM Review, 46 (2). pp. 354-356. ISSN 0036-1445

Higham, D.J. (2002) Nine ways to implement the binomial method for option valuation in MATLAB. SIAM Review, 44 (4). pp. 661-677. ISSN 0036-1445

Higham, D.J. (2001) An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Review, 43 (3). pp. 525-546. ISSN 0036-1445

Mackenzie, John A. (2001) Book review of robust computational techniques for boundary layers. SIAM Review, 43 (3). pp. 563-565. ISSN 0036-1445

McBride, A.C. (2001) The 2000 International Mathematical Olympiad. SIAM Review, 30. pp. 19-21. ISSN 0036-1445

McBride, A.C. (2001) What is the next number in the sequence? SIAM Review, 30. pp. 28-31. ISSN 0036-1445

This list was generated on Mon Aug 3 07:51:48 2020 BST.