Mark Bartlett
Cited by
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Does good ESG lead to better financial performances by firms? Machine learning and logistic regression models of public enterprises in Europe
C De Lucia, P Pazienza, M Bartlett
Sustainability 12 (13), 5317, 2020
Integer linear programming for the Bayesian network structure learning problem
M Bartlett, J Cussens
Artificial Intelligence 244, 258-271, 2017
Advances in Bayesian network learning using integer programming
M Bartlett, J Cussens
Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 13 …, 2013
Bayesian network structure learning with integer programming: Polytopes, facets and complexity
J Cussens, M Järvisalo, JH Korhonen, M Bartlett
Journal of Artificial Intelligence Research 58, 185-229, 2017
The temporal knapsack problem and its solution
M Bartlett, AM Frisch, Y Hamadi, I Miguel, SA Tarim, C Unsworth
Integration of AI and OR Techniques in Constraint Programming for …, 2005
Maximum likelihood pedigree reconstruction using integer linear programming
J Cussens, M Bartlett, EM Jones, NA Sheehan
Genetic epidemiology 37 (1), 69-83, 2013
Landscape gene flow, coexistence and threshold effect: the case of genetically modified herbicide tolerant oilseed rape (Brassica napus)
MG Ceddia, M Bartlett, C Perrings
Ecological Modelling 205 (1-2), 169-180, 2007
Quantifying the effect of buffer zones, crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level
MG Ceddia, M Bartlett, C Perrings
Agriculture, ecosystems & environment 129 (1-3), 65-72, 2009
Comparison of international normalized ratio audit parameters in patients enrolled in GARFIELD‐AF and treated with vitamin K antagonists
DA Fitzmaurice, G Accetta, S Haas, G Kayani, H Lucas Luciardi, ...
British journal of haematology 174 (4), 610-623, 2016
On the regulation of spatial externalities: coexistence between GM and conventional crops in the EU and the ‘newcomer principle’
MG Ceddia, M Bartlett, C De Lucia, C Perrings
Australian Journal of Agricultural and Resource Economics 55 (1), 126-143, 2011
The origins of syntax: from navigation to language
M Bartlett, D Kazakov
Connection Science 17 (3-4), 271-288, 2005
The role of environment structure in multi-agent simulations of language evolution
M Bartlett, D Kazakov
AISB 2004 Convention, 2, 2004
Prediction of casing critical buckling during shale gas hydraulic fracturing
AI Mohammed, B Oyeneyin, M Bartlett, J Njuguna
Journal of Petroleum Science and Engineering 185, 106655, 2020
Implementing a biofuel economy in the EU: Lessons from the SUSTOIL project and future perspectives for next generation biofuels
C De Lucia, M Bartlett
Renewable and Sustainable Energy Reviews 29, 22-30, 2014
Improved maximum likelihood reconstruction of complex multi-generational pedigrees
NA Sheehan, M Bartlett, J Cussens
Theoretical population biology 97, 11-19, 2014
An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation
AI Mohammed, M Bartlett, B Oyeneyin, K Kayvantash, J Njuguna
Journal of natural gas science and engineering 95, 104221, 2021
Guaranteed loop bound identification from program traces for WCET
M Bartlett, I Bate, D Kazakov
2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium …, 2009
Hierarchical agglomerative clustering for cross-language information retrieval
R Alfred, D Kazakov, M Bartlett, E Paskaleva
Int J Transl 19 (1), 139-162, 2007
Cooperative navigation and the faculty of language
D Kazakov, M Bartlett
Applied Artificial Intelligence 18 (9-10), 885-901, 2004
A multi-agent simulation of the evolution of language
D Kazakov, M Bartlett
Proceedings of Information Society Conference IS, 39-41, 2002
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