2 citations · 4 across the 4 of their papers we have counts for
9 papers
Disaster mapping from satellites: damage detection with crowdsourced point labels
Danil Kuzin, Olga Isupova, Brooke D. Simmons +1
High-resolution satellite imagery available immediately after disaster events is crucial for response planning as it facilitates broad situational awareness of critical infrastruct…
Using Echo State Networks to Approximate Value Functions for Control
Allen G. Hart, Kevin R. Olding, A. M. G. Cox +2
An Echo State Network (ESN) is a type of single-layer recurrent neural network with randomly-chosen internal weights and a trainable output layer. We prove under mild conditions th…
Mining and Tailings Dam Detection In Satellite Imagery Using Deep Learning
Remis Balaniuk, Olga Isupova, Steven Reece
This work explores the combination of free cloud computing, free open-source software, and deep learning methods to analyse a real, large-scale problem: the automatic country-wide…
Uncertainty propagation in neural networks for sparse coding
Danil Kuzin, Olga Isupova, Lyudmila Mihaylova
A novel method to propagate uncertainty through the soft-thresholding nonlinearity is proposed in this paper. At every layer the current distribution of the target vector is repres…
BCCNet: Bayesian classifier combination neural network
Olga Isupova, Yunpeng Li, Danil Kuzin +3
Machine learning research for developing countries can demonstrate clear sustainable impact by delivering actionable and timely information to in-country government organisations (…
Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors
Danil Kuzin, Olga Isupova, Lyudmila Mihaylova
This paper introduces a new sparse spatio-temporal structured Gaussian process regression framework for online and offline Bayesian inference. This is the first framework that give…