Mayo, David

10 publications

NeurIPS 2025 Training the Untrainable: Introducing Inductive Bias via Representational Alignment Vighnesh Subramaniam, David Mayo, Colin Conwell, Tomaso Poggio, Boris Katz, Brian Cheung, Andrei Barbu

NeurIPS 2024 BrainBits: How Much of the Brain Are Generative Reconstruction Methods Using? David Mayo, Christopher Wang, Asa Harbin, Abdulrahman Alabdulkareem, Albert Shaw, Boris Katz, Andrei Barbu

NeurIPS 2023 How Hard Are Computer Vision Datasets? Calibrating Dataset Difficulty to Viewing Time David Mayo, Jesse Cummings, Xinyu Lin, Dan Gutfreund, Boris Katz, Andrei Barbu

ICLR 2023 Learning in Temporally Structured Environments Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin Fathy Elsayed, Katherine Hermann, David Mayo, Michael Curtis Mozer

ICMLW 2022 Growing ObjectNet: Adding Speech, VQA, Occlusion, and Measuring Dataset Difficulty David Mayo, David Lu, Chris Zhang, Jesse Cummings, Xinyu Lin, Boris Katz, James R. Glass, Andrei Barbu

NeurIPSW 2022 Image Recognition Time for Humans Predicts Adversarial Vulnerability for Models David Mayo, Jesse Cummings, Xinyu Lin, Boris Katz, Andrei Barbu

NeurIPSW 2022 Workshop Version: How Hard Are Computer Vision Datasets? Calibrating Dataset Difficulty to Viewing Time David Mayo, Jesse Cummings, Xinyu Lin, Dan Gutfreund, Boris Katz, Andrei Barbu

NeurIPS 2021 Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex Colin Conwell, David Mayo, Andrei Barbu, Michael Buice, George Alvarez, Boris Katz

NeurIPSW 2021 On the Use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation Binxu Wang, David Mayo, Arturo Deza, Andrei Barbu, Colin Conwell

NeurIPS 2019 ObjectNet: A Large-Scale Bias-Controlled Dataset for Pushing the Limits of Object Recognition Models Andrei Barbu, David Mayo, Julian Alverio, William Luo, Christopher Wang, Dan Gutfreund, Josh Tenenbaum, Boris Katz