| 2022 | AIME | Malignant Mesothelioma Subtyping of Tissue Images via Sampling Driven Multiple Instance Prediction. | Mark Eastwood, Silviu Tudor Marc, Xiaohong W. Gao, Heba Sailem, Judith Offman, Emmanouil Karteris, Angeles Montero Fernandez, Danny Jonigk, William Cookson, Miriam Moffatt, Sanjay Popat, Fayyaz A. Minhas, Jan Lukas Robertus |
| 2018 | DASC | Unifying and Analysing Activities of Daily Living in Extra Care Homes. | Alexandros Konios, Yanguo Jing, Mark Eastwood, Bo Tan |
| 2018 | ICONIP | Deep Learning for Real Time Facial Expression Recognition in Social Robots. | Ariel Ruiz-Garcia, Nicola Webb, Vasile Palade, Mark Eastwood, Mark Elshaw |
| 2018 | IJCNN | Deep CNNs with Rotational Filters for Rotation Invariant Character Recognition. | Erik Barrow, Mark Eastwood, Chrisina Jayne |
| 2016 | ICONIP | Selective Dropout for Deep Neural Networks. | Erik Barrow, Mark Eastwood, Chrisina Jayne |
| 2015 | ICONIP | Deep Dropout Artificial Neural Networks for Recognising Digits and Characters in Natural Images. | Erik Barrow, Chrisina Jayne, Mark Eastwood |
| 2014 | IJCNN | Dual Deep Neural Network approach to matching data in different modes. | Mark Eastwood, Chrisina Jayne |
| 2014 | IDA | From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors. | Marcin Budka, Mark Eastwood, Bogdan Gabrys, Petr Kadlec, Manuel Martin Salvador, Stephanie Schwan, Athanasios Tsakonas, Indre Zliobaite |
| 2013 | IJCNN | Restricted Boltzmann machines for pre-training deep Gaussian networks. | Mark Eastwood, Chrisina Jayne |
| 2011 | ICDM | Interpretable, Online Soft-Sensors for Process Control. | Mark Eastwood, Petr Kadlec |
| 2009 | KES | A Non-sequential Representation of Sequential Data for Churn Prediction. | Mark Eastwood, Bogdan Gabrys |