| 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, ... Advances in Neural Information Processing Systems 32, 2019 | 634 | 2019 |
| Learning a natural-language to LTL executable semantic parser for grounded robotics C Wang, C Ross, YL Kuo, B Katz, A Barbu Conference on Robot Learning, 1706-1718, 2021 | 43 | 2021 |
| BrainBERT: Self-supervised representation learning for intracranial recordings C Wang, V Subramaniam, AU Yaari, G Kreiman, B Katz, I Cases, A Barbu International Conference on Learning Representations, 2023 | 28 | 2023 |
| Revealing Vision-Language Integration in the Brain with Multimodal Networks V Subramaniam, C Conwell, C Wang, G Kreiman, B Katz, I Cases, ... International Conference on Machine Learning, 2024 | 4 | 2024 |
| Population Transformer: Learning Population-level Representations of Intracranial Activity G Chau, C Wang, S Talukder, V Subramaniam, S Soedarmadji, Y Yue, ... ArXiv, 2024 | 1 | 2024 |
| Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli C Wang, AU Yaari, AK Singh, V Subramaniam, D Rosenfarb, J DeWitt, ... Advances in Neural Information Processing Systems, 2024 | | 2024 |
| 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 Advances in Neural Information Processing Systems, 2024 | | 2024 |
| Workshop Submission: Using Multimodal DNNs to Study Vision-Language Integration in the Brain V Subramaniam, C Conwell, C Wang, G Kreiman, B Katz, I Cases, ... ICLR 2023 Workshop on Multimodal Representation Learning: Perks and Pitfalls, 2023 | | 2023 |
| Weakly supervised semantic parsing for Linear Temporal Logic CZ Wang Massachusetts Institute of Technology, 2020 | | 2020 |
Andrei BarbuMIT, CSAILVerified email at 0xab.com
