Standley, T., Gao, R., Chen, D., Wu, J. & Savarese S. (2023). An Extensible Multimodal Multi-task Object Dataset with Materials (ICLR).

Standley, T., Zamir A., Chen, D., Guibas L., Malik, J. & Savarese S. (2020). Which Tasks Should be Learned Together in Multi-Task Learning? (ICML)

Standley, T., Sener, O., Chen, D. & Savarese S. (2017). image2mass: Estimating the Mass of an Object from Its Image Proceedings of the 1st Annual Conference on Robot Learning (CoRL), in PMLR 78:324-333 (Long Talk)

Hall, C., Standley, T., & Hollerer, t. (2017). Infra: structure all the way down: structured data as a visual programming language. Proceedings of the 2017 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward!), ACM, New York, NY, USA, 180-197.

Standley, T., & Korf, R. (2011). Complete Algorithms for Cooperative Pathfinding Problems. Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-11), Barcelona, Catalonia, Spain, pages 668-673.

Standley, T. (2010). Finding Optimal Solutions to Cooperative Pathfinding Problems. In proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI), pages 173-178.

Choi, A., Standley, T & Darwiche, A. (2009). Approximating Weighted Max-SAT Problems by Compensating for Relaxations. In Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming (CP), pages 211-225.

Workshops and Theses

Standley, T. (2012). Independence Detection for Multi-Agent Pathfinding Problems. In Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence (WoMP).

Standley, T. (2010). Optimal and Anytime Approximation Algorithms for Cooperative Pathfinding Problems. MS Thesis. University of California, Los Angeles.