581 citations · 1.5k across the 48 of their papers we have counts for
72 papers
Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation
Muhammed Razzak, Gonzalo Mateo-Garcia, Luis Gómez-Chova +2
High resolution remote sensing imagery is used in broad range of tasks, including detection and classification of objects. High-resolution imagery is however expensive, while lower…
Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific
Andrew Jesson, Peter Manshausen, Alyson Douglas +3
Aerosol-cloud interactions include a myriad of effects that all begin when aerosol enters a cloud and acts as cloud condensation nuclei (CCN). An increase in CCN results in a decre…
Deep Deterministic Uncertainty for Semantic Segmentation
Jishnu Mukhoti, Joost van Amersfoort, Philip H. S. Torr +1
We extend Deep Deterministic Uncertainty (DDU), a method for uncertainty estimation using feature space densities, to semantic segmentation. DDU enables quantifying and disentangli…
GeneDisco: A Benchmark for Experimental Design in Drug Discovery
Arash Mehrjou, Ashkan Soleymani, Andrew Jesson +4
In vitro cellular experimentation with genetic interventions, using for example CRISPR technologies, is an essential step in early-stage drug discovery and target validation that s…
Quantifying Uncertainty for Machine Learning Based Diagnostic
Owen Convery, Lewis Smith, Yarin Gal +1
Virtual Diagnostic (VD) is a deep learning tool that can be used to predict a diagnostic output. VDs are especially useful in systems where measuring the output is invasive, limite…
Improving black-box optimization in VAE latent space using decoder uncertainty
Pascal Notin, José Miguel Hernández-Lobato, Yarin Gal
Optimization in the latent space of variational autoencoders is a promising approach to generate high-dimensional discrete objects that maximize an expensive black-box property (e.…