| 2022 | IJCNN | Spiking Approximations of the MaxPooling Operation in Deep SNNs. | Ramashish Gaurav, Bryan P. Tripp, Apurva Narayan |
| 2021 | AI | Driving Scene Understanding: How much temporal context and spatial resolution is necessary? | Ramashish Gaurav, Bryan P. Tripp, Apurva Narayan |
| 2019 | CISS | Figure-ground representation in deep neural networks. | Brian Hu, Salman Khan, Ernst Niebur, Bryan P. Tripp |
| 2017 | IJCNN | Similarities and differences between stimulus tuning in the inferotemporal visual cortex and convolutional networks. | Bryan P. Tripp |
| 2016 | CogSci | A scaleable spiking neural model of action planning. | Peter Blouw, Chris Eliasmith, Bryan P. Tripp |
| 2016 | ICANN | Real-Time FPGA Simulation of Surrogate Models of Large Spiking Networks. | Murphy Berzish, Chris Eliasmith, Bryan P. Tripp |
| 2016 | ICANN | How Is Scene Recognition in a Convolutional Network Related to that in the Human Visual System? | Sugandha Sharma, Bryan P. Tripp |
| 2016 | ICANN | A Convolutional Network Model of the Primate Middle Temporal Area. | Bryan P. Tripp |
| 2014 | ECCV | Modelling Primate Control of Grasping for Robotics Applications. | Ashley Kleinhans, Serge Thill, Benjamin Rosman, Renaud Detry, Bryan P. Tripp |
| 2000 | AMIA | Clinical Computing: Enriching the Canopy. | Bryan P. Tripp, Matthew W. Morgan |
| 1999 | AMIA | Getting data out of the electronic patient record: critical steps in building a data warehouse for decision support. | A. Ebidia, Carol Mulder, Bryan P. Tripp, Matthew W. Morgan |