Scan-less machine-learning-enabled incoherent microscopy for minimally-invasive deep-brain imaging R Guo, S Nelson, M Regier, MW Davis, EM Jorgensen, J Shepherd, ... Optics Express 30 (2), 1546-1554, 2022 | 11 | 2022 |
Bijective-constrained cycle-consistent deep learning for optics-free imaging and classification S Nelson, R Menon Optica 9 (1), 26-31, 2022 | 7 | 2022 |
Needle-based deep-neural-network camera R Guo, S Nelson, R Menon Applied Optics 60 (10), B135-B140, 2021 | 6 | 2021 |
Optics-free imaging of complex, non-sparse and color QR-codes with deep neural networks S Nelson, E Scullion, R Menon OSA continuum 3 (9), 2423-2428, 2020 | 5* | 2020 |
Computational microscopy for fast widefield deep-tissue fluorescence imaging using a commercial dual-cannula probe E Mitra, R Guo, S Nelson, N Nagarajan, R Menon Optics continuum 1 (9), 2091-2099, 2022 | 3 | 2022 |
Learning to compose superweights for neural parameter allocation search P Teterwak, S Nelson, N Dryden, D Bashkirova, K Saenko, BA Plummer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 2 | 2024 |
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters C Pham, P Teterwak, S Nelson, BA Plummer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 1 | 2024 |
Optics-free imaging using a self-consistent supervised deep neural network S Nelson, R Menon Optical Sensors, JTu5A. 3, 2021 | 1 | 2021 |
Needle-based deep-neural-network imaging method R Guo, S Nelson, E Mitra, R Menon Imaging Systems and Applications, ITh5D. 3, 2021 | 1 | 2021 |
Classification of optics-free images with deep neural networks S Nelson, R Menon arXiv preprint arXiv:2011.05132, 2020 | 1 | 2020 |
Learning to Compose SuperWeights for Neural Parameter Allocation Search Supplementary P Teterwak, S Nelson, N Dryden, D Bashkirova, K Saenko, BA Plummer | | |
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters Supplementary C Pham, P Teterwak, S Nelson, BA Plummer | | |
SuperWeight Ensembles: Automated Compositional Parameter Sharing Across Diverse Architechtures P Teterwak, S Nelson, N Dryden, D Bashkirova, K Saenko, BA Plummer | | |