TENNLab - Neuromorphic Architectures, Learning, Applications
We are a group of faculty, post-docs, graduate students and undergraduates researching a new paradigm of computing, inspired by the human brain. Our research encompasses nearly every facet of the area, including current and emergent hardware implementations, theoretical models, programming techniques and applications. (Read More)
- Non-Traditional Input Encoding Schemes for Spiking Neuromorphic Systems: IJCNN: The International Joint Conference on Neural Networks July, 2019.
- Intelligent Reservoir Generation for Liquid State Machines using Evolutionary Optimization: IJCNN: The International Joint Conference on Neural Networks July, 2019.
- Spike-based primitives for graph algorithms: Published on arXiv. March, 2019.
- The TENNLab Suite of LIDAR-Based Control Applications for Recurrent, Spiking, Neuromorphic Systems: 44th Annual GOMACTech Conference March, 2019.
- Adapting Spiking Networks to Neuromorphic Hardware Subject to Process Variability: 44th Annual GOMACTech Conference March, 2019.