2 citations · 3 across the 7 of their papers we have counts for
9 papers
SkillFusion: Towards Reliable Multi-Skill Composition for LLM Agents
Enhao Huang, Xinye Zhao, Yiming Li +5
Independently authored skills can impose incompatible requirements, competing preferences, and redundant instructions when jointly loaded by an LLM agent. We propose SkillFusion, a…
Hierarchical Graph Networks for Accurate Weather Forecasting via Lightweight Training
Thomas Bailie, S. Karthik Mukkavilli, Varvara Vetrova +1
Climate events arise from intricate, multivariate dynamics governed by global-scale drivers, profoundly impacting food, energy, and infrastructure. Yet, accurate weather prediction…
Reducing Smoothness with Expressive Memory Enhanced Hierarchical Graph Neural Networks
Thomas Bailie, Yun Sing Koh, S. Karthik Mukkavilli +1
Graphical forecasting models learn the structure of time series data via projecting onto a graph, with recent techniques capturing spatial-temporal associations between variables v…
A Study on Monthly Marine Heatwave Forecasts in New Zealand: An Investigation of Imbalanced Regression Loss Functions with Neural Network Models
Ding Ning, Varvara Vetrova, Sébastien Delaux +3
Marine heatwaves (MHWs) are extreme ocean-temperature events with significant impacts on marine ecosystems and related industries. Accurate forecasts (one to six months ahead) of M…
Diving Deep: Forecasting Sea Surface Temperatures and Anomalies
Ding Ning, Varvara Vetrova, Karin R. Bryan +4
This overview paper details the findings from the Diving Deep: Forecasting Sea Surface Temperatures and Anomalies Challenge at the European Conference on Machine Learning and Princ…
Advancing Marine Heatwave Forecasts: An Integrated Deep Learning Approach
Ding Ning, Varvara Vetrova, Yun Sing Koh +1
Marine heatwaves (MHWs), an extreme climate phenomenon, pose significant challenges to marine ecosystems and industries, with their frequency and intensity increasing due to climat…
Selective nonlinearities removal from digital signals
Krzysztof A. Maliszewski, Magdalena A. Urbanska, Varvara Vetrova +1
Many instruments performing optical and non-optical imaging and sensing, such as Optical Coherence Tomography (OCT), Magnetic Resonance Imaging or Fourier-transform spectrometry, p…
Graph-Based Deep Learning for Sea Surface Temperature Forecasts
Ding Ning, Varvara Vetrova, Karin R. Bryan
Sea surface temperature (SST) forecasts help with managing the marine ecosystem and the aquaculture impacted by anthropogenic climate change. Numerical dynamical models are resourc…
Towards retrieving dispersion profiles using quantum-mimic Optical Coherence Tomography and Machine Learnin
Krzysztof A. Maliszewski, Piotr Kolenderski, Varvara Vetrova +1
Artefacts in quantum-mimic Optical Coherence Tomography are considered detrimental because they scramble the images even for the simplest objects. They are a side effect of autocor…