Machine Learning

Maier-Hein, L., Reinke, A., Godau, P., et al. (2024). Metrics reloaded: recommendations for image analysis validation. Nature Methods, 21(2), 195-212. doi: 10.1038/s41592-023-02151-z    There is growing evidence that problems with validating machine learning (ML) algorithms are a global issue that’s often overlooked. Read More

Kolouri, S., Naderializadeh, N., Rohde, G. K., & Hoffmann, H. (2021). WASSERSTEIN EMBEDDING FOR GRAPH LEARNING. ICLR 2021 – 9th International Conference on Learning Representations, 34. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150286096&partnerID=40&md5=8b88e110167be2c5fd01da171324d3d6  We introduce a new method called Wasserstein Embedding for Graph Learning (WEGL), which is a… Read More

Lin, J.-R., Wang, S., Coy, S., Chen, Y.-A., Yapp, C., Tyler, M., Nariya, M. K., Heiser, C. N., Lau, K. S., Santagata, S., & Sorger, P. K. (2023). Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer. Cell, 186(2), 363-381.e13. doi: 10.1016/j.cell.2022.12.028  … Read More

Davalos, Eduardo; Zhang, Yike; Ashwin, T.S.; Fonteles, Joyce Horn; Timalsina, Umesh; Biswas, Gautam. “3D Gaze Tracking for Studying Collaborative Interactions in Mixed-Reality Environments”. ACM International Conference Proceeding Series, 2024, pp. 175-183. DOI: 10.1145/3686215.3688380.    This study presents a new method for tracking where people are looking in… Read More

Fang, Zihan; Huang, Yu. “‘Math is a pain!’: Understanding challenges and needs of the Machine Learning community on Stack Overflow“. Proceedings of the ACM on Human-Computer Interaction, vol. 8, no. CSCW2, 2024, p. 451. DOI: 10.1145/3686990.    Stack Overflow (SO)… Read More

Karim, Helmet T.; Gerlach, Andrew; Butters, Meryl A.; Krafty, Robert; Boyd, Brian D.; Banihashemi, Layla; Landman, Bennett A.; Ajilore, Olusola; Taylor, Warren D.; Andreescu, Carmen. “Brain Age Is Not a Significant Predictor of Relapse Risk in Late-Life Depression“. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2024. Read More

Tang, N., Chen, M., Ning, Z., Bansal, A., Huang, Y., McMillan, C., Li, T.J.-J., “Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking,” Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC, 2024, pp. 40-46, DOI: 10.1109/VL/HCC60511.2024.00015. Read More

Zhang, Y.; Huang, Y.; Rosen, A.; Jiang, L.G.; McCarty, M.; RoyChoudhury, A.; Han, J.H.; Wright, A.; Ancker, J.S.; Steel, P.A.D. “Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions.” PLOS Digital Health, Volume 3, Issue… Read More

Cohn, C.; Snyder, C.; Fonteles, J.H.; Ashwin, T.S.; Montenegro, J.; Biswas, G. “A multimodal approach to support teacher, researcher and AI collaboration in STEM+C learning environments.” British Journal of Educational Technology, 2024, DOI: 10.1111/bjet.13518.    Advances in generative AI and multimodal learning analytics… Read More