Smith, Lewis

Towards global flood mapping onboard low cost satellites with machine learning

Mateo-Garcia, G., Veitch-Michaelis, J., Smith, L., Oprea, S. V., Schumann, G., Gal, Y., Baydin, A. G., & Backes, D. (2021) · Scientific Reports

Flood Risk Assessment and ManagementRemote-Sensing Image Classification

Cited by 202

Galaxy Zoo: probabilistic morphology through Bayesian CNNs and active learning

Walmsley, M., Smith, L., Lintott, C., Gal, Y., Bamford, S., Dickinson, H., Fortson, L., Kruk, S., Masters, K., Scarlata, C., et al. (2020) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 160

Improving Dictionary Learning with Gated Sparse Autoencoders

Rajamanoharan, S., Conmy, A., Smith, L., Lieberum, T., Varma, V., Kramár, J., Shah, R., & Nanda, N. (2024) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 3

Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Lieberum, T., Rajamanoharan, S., Conmy, A., Smith, L., Sonnerat, N., Varma, V., Kramár, J., Dragan, A., Shah, R., & Nanda, N. (2024) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 2