| What's hidden in a randomly weighted neural network? V Ramanujan*, M Wortsman*, A Kembhavi, A Farhadi, M Rastegari Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 402 | 2020 |
| Datacomp: In search of the next generation of multimodal datasets SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ... Advances in Neural Information Processing Systems 36, 27092-27112, 2023 | 388 | 2023 |
| Supermasks in superposition M Wortsman*, V Ramanujan*, R Liu, A Kembhavi, M Rastegari, J Yosinski, ... Advances in Neural Information Processing Systems 33, 15173-15184, 2020 | 344 | 2020 |
| Soft threshold weight reparameterization for learnable sparsity A Kusupati, V Ramanujan, R Somani, M Wortsman, P Jain, S Kakade, ... International Conference on Machine Learning, 5544-5555, 2020 | 259 | 2020 |
| Matryoshka representations for adaptive deployment A Kusupati, G Bhatt, A Rege, M Wallingford, A Sinha, V Ramanujan, ... arXiv preprint arXiv:2205.13147 3, 2022 | 126* | 2022 |
| Improving shape deformation in unsupervised image-to-image translation A Gokaslan, V Ramanujan, D Ritchie, KI Kim, J Tompkin Proceedings of the European Conference on Computer Vision (ECCV), 649-665, 2018 | 96 | 2018 |
| Effects of parameter norm growth during transformer training: Inductive bias from gradient descent W Merrill, V Ramanujan, Y Goldberg, R Schwartz, N Smith arXiv preprint arXiv:2010.09697, 2020 | 37 | 2020 |
| Forward compatible training for representation learning V Ramanujan, PKA Vasu, A Farhadi, O Tuzel, H Pouransari arXiv preprint arXiv:2112.02805, 2021 | 25* | 2021 |
| On the connection between pre-training data diversity and fine-tuning robustness V Ramanujan, T Nguyen, S Oh, A Farhadi, L Schmidt Advances in Neural Information Processing Systems 36, 66426-66437, 2023 | 21 | 2023 |
| Neural Priming for Sample-Efficient Adaptation M Wallingford*, V Ramanujan*, A Fang, A Kusupati, R Mottaghi, ... arXiv preprint arXiv:2306.10191, 2023 | 12 | 2023 |
| Llc: Accurate, multi-purpose learnt low-dimensional binary codes A Kusupati, M Wallingford, V Ramanujan, R Somani, JS Park, K Pillutla, ... Advances in neural information processing systems 34, 23900-23913, 2021 | 12 | 2021 |
| Neural radiance field codebooks M Wallingford, A Kusupati, A Fang, V Ramanujan, A Kembhavi, ... arXiv preprint arXiv:2301.04101, 2023 | 10 | 2023 |
| The unmet promise of synthetic training images: Using retrieved real images performs better S Geng, CY Hsieh, V Ramanujan, M Wallingford, CL Li, PWW Koh, ... Advances in Neural Information Processing Systems 37, 7902-7929, 2024 | 3 | 2024 |
| Data Curation for Large Scale Detection Pretraining V Ramanujan, H Zhang, Y Yang, A Farhadi, AT Toshev, L Schmidt, ... | 1 | 2023 |
| When Worse is Better: Navigating the compression-generation tradeoff in visual tokenization V Ramanujan, K Tirumala, A Aghajanyan, L Zettlemoyer, A Farhadi arXiv preprint arXiv:2412.16326, 2024 | | 2024 |
| From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos M Wallingford, A Bhattad, A Kusupati, V Ramanujan, M Deitke, ... Advances in Neural Information Processing Systems 37, 17743-17760, 2024 | | 2024 |
| On the Connection between Pre-training Data Diversity and Robustness V Ramanujan, T Nguyen, L Schmidt, A Farhadi First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at …, 0 | | |
Ali FarhadiProfessor, Computer Science and Engineering, University of WashingtonEmail confirmado em cs.uw.edu