118 citations · 216 across the 30 of their papers we have counts for
8 papers · 1 filter
A Station-Based Evaluation of Machine Learning-based Weather Forecasting Models in Northern Norway
Siyan Chen, Lars Uebbing, Eirik Mikal Samuelsen +5
Recent machine learning weather prediction (MLWP) models have demonstrated remarkable forecasting skill on global reanalysis-based benchmarks. However, their performance remains un…
Group-Equivariant Poincaré Convolutional Networks
Aiden Durrant, Rahul Baburajan, Georgios Leontidis
While recent methods like that of the Poincaré ResNet have demonstrated the ability to learning visual representations directly in hyperbolic space, their optimisation remains a ch…
CrevasseSeg: A Label-Efficient UAV Crevasse Segmentation Framework
Steven Wallace, William D. Harcourt, Richard Hann +3
Crevasse mapping from uncrewed aerial vehicle (UAV) imagery matters for glaciological research and for field safety in glaciated terrain. Yet, pixel-level annotation of glacier sur…
Causal State-Space Model for Causal Inference: Estimating Longitudinal Individual Treatment Effects
Abisoye Abidakun, Mingjun Zhong, Georgios Leontidis
Estimating counterfactual outcomes over time from longitudinal observational data is central to clinical decision support. Existing methods rely on domain confusion -- adversarial…
Trust-Aware Predictive Emissions Monitoring for Gas Turbine Fleets with Limited Labelled Data
Rebecca Potts, Aiden Durrant, Rick Hackney +1
Machine learning-based predictive emissions monitoring systems offer a practical alternative to direct emissions measurement, but their deployment across gas turbine fleets is chal…
NOFE - Neural Operator Function Embedding
Lars Uebbing, Harald L. Joakimsen, Siyan Chen +6
Most dimensionality reduction methods treat data as discrete point clouds, ignoring the continuous domain structure inherent to many real-world processes. To bridge this gap, we in…
Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts
Matthew Beddows, Aiden Durrant, Georgios Leontidis
Accurate crop yield forecasting in commercial soft fruit production is constrained by the data available in typical commercial farm records, which lack the sensor networks, satelli…
HiAP: A Multi-Granular Stochastic Auto-Pruning Framework for Vision Transformers
Andy Li, Aiden Durrant, Milan Markovic +1
Vision Transformers require significant computational resources and memory bandwidth, severely limiting their deployment on resource-constraint hardware. Most structured pruning me…