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David Mayo
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2020 – today
- 2023
- [c7]David Mayo, Tyler R. Scott, Mengye Ren, Gamaledin Elsayed, Katherine L. Hermann, Matt Jones, Michael Mozer:
Multitask Learning Via Interleaving: A Neural Network Investigation. CogSci 2023 - [c6]Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin Fathy Elsayed, Katherine L. Hermann, David Mayo, Michael Curtis Mozer:
Learning in temporally structured environments. ICLR 2023 - [c5]David Mayo, Jesse Cummings, Xinyu Lin, Dan Gutfreund, Boris Katz, Andrei Barbu:
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time. NeurIPS 2023 - 2022
- [c4]David Mayo, Heba Elgazzar:
Predicting Cryptocurrency Price Change Direction from Supply-Side Factors via Machine Learning Methods. AIIoT 2022: 330-336 - [i2]Vijay Gadepally, Gregory Angelides, Andrei Barbu, Andrew Bowne, Laura J. Brattain, Tamara Broderick, Armando Cabrera, Glenn Carl, Ronisha Carter, Miriam Cha, Emilie Cowen, Jesse Cummings, Bill Freeman, James R. Glass, Sam Goldberg, Mark Hamilton, Thomas Heldt, Kuan Wei Huang, Phillip Isola, Boris Katz, Jamie Koerner, Yen-Chen Lin, David Mayo, Kyle McAlpin, Taylor Perron, Jean E. Piou, Hrishikesh M. Rao, Hayley Reynolds, Kaira Samuel, Siddharth Samsi, Morgan Schmidt, Leslie Shing, Olga Simek, Brandon Swenson, Vivienne Sze, Jonathan Taylor, Paul Tylkin, Mark Veillette, Matthew L. Weiss, Allan B. Wollaber, Sophia Yuditskaya, Jeremy Kepner:
Developing a Series of AI Challenges for the United States Department of the Air Force. CoRR abs/2207.07033 (2022) - 2021
- [c3]Colin Conwell, David Mayo, Andrei Barbu, Michael A. Buice, George Alvarez, Boris Katz:
Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex. NeurIPS 2021: 5590-5607 - [i1]Binxu Wang, David Mayo, Arturo Deza, Andrei Barbu, Colin Conwell:
On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation. CoRR abs/2112.07173 (2021)
2010 – 2019
- 2019
- [c2]Andrei Barbu, David Mayo, Julian Alverio, William Luo, Christopher Wang, Dan Gutfreund, Josh Tenenbaum, Boris Katz:
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models. NeurIPS 2019: 9448-9458 - 2016
- [c1]Scott W. Greenwald, Markus Funk, Luke Loreti, David Mayo, Pattie Maes:
EVA: Exploratory Learning with Virtual Companions Sharing Attention and Context. ICALT 2016: 26-30
Coauthor Index
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