| 2016 | IJCNN | Virtual drug screening using neural networks. | Daniel M. Hagan, Martin T. Hagan |
| 2015 | ICIP | A computational model for predicting local distortion visibility via convolutional neural network trainedon natural scenes. | Md Mushfiqul Alam, Pranita Patil, Martin T. Hagan, Damon M. Chandler |
| 2015 | IJCNN | Enhanced recurrent network training. | Amir H. Jafari, Martin T. Hagan |
| 2013 | IJCNN | A procedure for training recurrent networks. | Manh Cong Phan, Mark H. Beale, Martin T. Hagan |
| 2009 | IJCNN | Realizing general MLP networks with minimal FPGA resources. | Carl Latino, Marco A. Moreno-Armendriz, Martin T. Hagan |
| 2002 | ICMLA | Neural Networks: Are Stochastic Global Optimization Methods Worth the Trouble? | Lonnie Hamm, B. Wade Brorsen, Martin T. Hagan |
| 1999 | IJCNN | Optimal use of regularization and cross-validation in neural network modeling. | Dingding Chen, Martin T. Hagan |
| 1999 | IJCNN | Recursive orthogonal least squares learning with automatic weight selection for Gaussian neural networks. | Meng H. Fun, Martin T. Hagan |
| 1999 | IJCNN | Online least-squares training for the underdetermined case. | Roger L. Schultz, Martin T. Hagan |
| 1999 | IJCNN | Training multi-loop networks. | Roger L. Schultz, Martin T. Hagan, Orlando De Jess |
| 1985 | ICPP | Parallel Signal Processing Research on the HEP. | Martin T. Hagan, Howard B. Demuth, Paul Hartono Singgih |