1. Conference contribution › Research › Peer-reviewed

2. Stateconet: Statistical ecology neural networks for species distribution modeling

   Seo, E., Hutchinson, R. A., Fu, X., Li, C., Hallman, T. A., Kilbride, J. & Robinson, W. D., 18 May 2021, Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 35. p. 513-521

   Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3. Paper › Research › Not peer-reviewed

4. On the role of spatial clustering algorithms in building species distribution models from community science data

   Roth, M., Hallman, T., Robinson, W. D. & Hutchinson, R., 2021.

   Research output: Contribution to conference › Paper

5. What are deep networks learning? A Comparison of Deep Learning and Traditional Summaries of Remotely Sensed Imagery

   Hopkins, L., Hallman, T. A., Kilbride, J. B., Robinson, W. D., Wong, W.-K. & Hutchinson, R. A., 14 Dec 2021.

   Research output: Contribution to conference › Paper

6. Paper › Research › Peer-reviewed
7. Published

   Model Evaluation for Geospatial Problems

   Wang, J., Hallman, T., Hopkins, L., Kilbride, J. B., Robinson, W. D. & Hutchinson, R., 30 Dec 2023.

   Research output: Contribution to conference › Paper › peer-review