| Beyond chinchilla-optimal: Accounting for inference in language model scaling laws N Sardana, J Portes, S Doubov, J Frankle arXiv preprint arXiv:2401.00448, 2023 | 28 | 2023 |
| Pit30m: A benchmark for global localization in the age of self-driving cars J Martinez, S Doubov, J Fan, S Wang, G Máttyus, R Urtasun 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 14 | 2020 |
| Scalable neural data server: A data recommender for transfer learning T Cao, SA Doubov, D Acuna, S Fidler Advances in Neural Information Processing Systems 34, 8984-8997, 2021 | 7 | 2021 |
| Localization with diverse dataset for autonomous vehicles JM Covarrubias, R Urtasun, S Wang, IA Barsan, GS Mattyus, A Doubov, ... US Patent 11,820,397, 2023 | 3 | 2023 |
| Sparse Upcycling: Inference Inefficient Finetuning S Doubov, N Sardana, V Chiley arXiv preprint arXiv:2411.08968, 2024 | | 2024 |
| How many trained neural networks are needed for influence estimation in modern deep learning? S Doubov, T Cao, D Acuna, S Fidler I Can't Believe It's Not Better Workshop: Understanding Deep Learning …, 0 | | |
| Studying BatchNorm Learning Rate Decay on Meta-Learning Inner-Loop Adaptation A Wang, S Doubov, G Leung Fifth Workshop on Meta-Learning at the Conference on Neural Information …, 0 | | |
