| A deep convolutional auto-encoder with pooling-unpooling layers in caffe V Turchenko, E Chalmers, A Luczak arXiv preprint arXiv:1701.04949, 2017 | 97 | 2017 |
| Learning to predict consequences as a method of knowledge transfer in reinforcement learning E Chalmers, EB Contreras, B Robertson, A Luczak, A Gruber IEEE transactions on neural networks and learning systems 29 (6), 2259-2270, 2017 | 49 | 2017 |
| Covering complete proteomes with X-ray structures: a current snapshot MJ Mizianty, X Fan, J Yan, E Chalmers, C Woloschuk, A Joachimiak, ... Acta Crystallographica Section D: Biological Crystallography 70 (11), 2781-2793, 2014 | 38 | 2014 |
| Predicting success or failure of brace treatment for adolescents with idiopathic scoliosis E Chalmers, L Westover, J Jacob, A Donauer, VH Zhao, EC Parent, ... Medical & biological engineering & computing 53, 1001-1009, 2015 | 24 | 2015 |
| An advanced compliance monitor for patients undergoing brace treatment for idiopathic scoliosis E Chalmers, E Lou, D Hill, HV Zhao Medical engineering & physics 37 (2), 203-209, 2015 | 24 | 2015 |
| Development of a pressure control system for brace treatment of scoliosis E Chalmers, E Lou, D Hill, VH Zhao, MS Wong IEEE Transactions on Neural Systems and Rehabilitation Engineering 20 (4 …, 2012 | 21 | 2012 |
| Inertial sensing algorithms for long-term foot angle monitoring for assessment of idiopathic toe-walking E Chalmers, J Le, D Sukhdeep, J Watt, J Andersen, E Lou Gait & posture 39 (1), 485-489, 2014 | 19 | 2014 |
| Computational properties of the hippocampus increase the efficiency of goal-directed foraging through hierarchical reinforcement learning E Chalmers, A Luczak, AJ Gruber Frontiers in computational neuroscience 10, 128, 2016 | 15 | 2016 |
| Prescriptive analytics applied to brace treatment for AIS: a pilot demonstration E Chalmers, D Hill, V Zhao, E Lou Scoliosis 10, 1-4, 2015 | 15 | 2015 |
| Context-switching and adaptation: Brain-inspired mechanisms for handling environmental changes E Chalmers, EB Contreras, B Robertson, A Luczak, A Gruber 2016 International Joint Conference on Neural Networks (IJCNN), 3522-3529, 2016 | 10 | 2016 |
| Human experts’ and a fuzzy model's predictions of outcomes of scoliosis treatment: A comparative analysis E Chalmers, W Pedrycz, E Lou IEEE Transactions on Biomedical Engineering 62 (3), 1001-1007, 2014 | 10 | 2014 |
| Toward maximum-predictive-value classification E Chalmers, M Mizianty, E Parent, Y Yuan, E Lou Pattern recognition 47 (12), 3949-3958, 2014 | 8 | 2014 |
| Predicting the outcome of brace treatment for scoliosis using conditional fuzzy clustering E Chalmers, W Pedrycz, E Lou 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 837-842, 2013 | 7 | 2013 |
| Machine Learning with Certainty: A Requirement for Intelligent Process Automation E Chalmers 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 5 | 2018 |
| A deep convolutional auto-encoder with pooling-unpooling layers in caffe. arXiv 2017 V Turchenko, E Chalmers, A Luczak arXiv preprint arXiv:1701.04949, 0 | 5 | |
| Biologically-inspired neuronal adaptation improves learning in neural networks Y Kubo, E Chalmers, A Luczak Communicative & Integrative Biology 16 (1), 2163131, 2023 | 3 | 2023 |
| Hippocluster: an efficient, hippocampus-inspired algorithm for graph clustering E Chalmers, AJ Gruber, A Luczak Information Sciences 639, 118999, 2023 | 3 | 2023 |
| Combining backpropagation with equilibrium propagation to improve an actor-critic reinforcement learning framework Y Kubo, E Chalmers, A Luczak Frontiers in Computational Neuroscience 16, 980613, 2022 | 3 | 2022 |
| Reinforcement learning with brain-inspired modulation can improve adaptation to environmental changes E Chalmers, A Luczak arXiv preprint arXiv:2205.09729, 2022 | 3 | 2022 |
| Biologically-inspired neuronal adaptation improves learning in neural networks Y Kubo, E Chalmers, A Luczak arXiv preprint arXiv:2204.14008, 2022 | 2 | 2022 |
