| Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models A Barbu, D Mayo, J Alverio, W Luo, C Wang, D Gutfreund, J Tenenbaum, ... NeurIPS 2019, 2019 | 647 | 2019 |
| Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex C Conwell, D Mayo, MA Buice, B Katz, GA Alvarez, A Barbu NeurIPS 2021, 2021 | 30 | 2021 |
| How hard are computer vision datasets? Calibrating dataset difficulty to viewing time D Mayo, J Cummings, X Lin, D Gutfreund, B Katz, A Barbu NeurIPS 2023, 2023 | 17 | 2023 |
| On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation B Wang, D Mayo, A Deza, A Barbu, C Conwell SVRHM 2021 Workshop@ NeurIPS, 2021 | 13 | 2021 |
| Eva: Exploratory learning with virtual companions sharing attention and context SW Greenwald, M Funk, L Loreti, D Mayo, P Maes 2016 IEEE 16th International Conference on Advanced Learning Technologies …, 2016 | 5 | 2016 |
| Multitask Learning Via Interleaving: A Neural Network Investigation D Mayo, TR Scott, M Ren, G Elsayed, K Hermann, M Jones, M Mozer Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45), 2023 | 4 | 2023 |
| Learning in temporally structured environments M Jones, TR Scott, M Ren, GF Elsayed, K Hermann, D Mayo, MC Mozer The Eleventh International Conference on Learning Representations, 2022 | 4 | 2022 |
| Developing a Series of AI Challenges for the United States Department of the Air Force V Gadepally, G Angelides, A Barbu, A Bowne, LJ Brattain, T Broderick, ... 2022 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2022 | 3 | 2022 |
| Neural network online training with sensitivity to multiscale temporal structure M Jones, D Mayo, T Scott, M Ren, G ElSayed, K Hermann, MC Mozer NeurIPS workshop on Memory in Artificial and Real Intelligence (MemARI), 2022 | 2 | 2022 |
| BrainBits: How Much of the Brain are Generative Reconstruction Methods Using? D Mayo, C Wang, A Harbin, A Alabdulkareem, AE Shaw, B Katz, A Barbu NeurIPS 2024, 2024 | | 2024 |
| Using Multimodal Deep Neural Networks to Disentangle Language from Visual Aesthetics C Conwell, C Hamblin, C Boccagno, D Mayo, J Cummings, L Isik, A Barbu arXiv preprint arXiv:2410.23603, 2024 | | 2024 |
| Training the Untrainable: Introducing Inductive Bias via Representational Alignment V Subramaniam, D Mayo, C Conwell, T Poggio, B Katz, B Cheung, ... arXiv preprint arXiv:2410.20035, 2024 | | 2024 |
| ObjectNet Captions: Models are not superhuman captioners J Cummings, D Mayo, IA Palmer, JR Glass, B Katz, A Barbu | | 2024 |
| Image recognition time for humans predicts adversarial vulnerability for models D Mayo, J Cummings, X Lin, B Katz, A Barbu ML Safety 2022 Workshop@ NeurIPS, 2022 | | 2022 |
| Workshop version: How hard are computer vision datasets? Calibrating dataset difficulty to viewing time D Mayo, J Cummings, X Lin, D Gutfreund, B Katz, A Barbu SVRHM 2022 Workshop@ NeurIPS, 2022 | | 2022 |
| Growing ObjectNet: Adding speech, VQA, occlusion, and measuring dataset difficulty D Mayo, D Lu, C Zhang, J Cummings, X Lin, B Katz, JR Glass, A Barbu ICML 2022 Shift Happens Workshop, 2022 | | 2022 |
| Understanding object recognition performance at scale in machines and humans DI Mayo Massachusetts Institute of Technology, 2019 | | 2019 |
Andrei BarbuMIT, CSAILBestätigte E-Mail-Adresse bei 0xab.com
