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DSTrain
Research Areas 2024 (Call 1)
Mathematics & Statistics
Bayesian machine learning
Causal Supervised Learning
Computational modelling of soft and complex interfaces
Deep Learning and Mathematical proof checking
Deep learning methods for approximating SPDE
Explainable statistical models
Financial trading and forecasting in energy markets
Foundations of physics informed neural networks
Risk, hedging and control via signatures and ML
Risk, reliability and machine learning
Rogue waves
Statistics and Machine Learning for Assessing Climate Risk
Sustainable and renewable offshore energy
DSTrain
>
Research Areas 2024 (Call 1)
>
Mathematics & Statistics
Mathematics & Statistics
Research Themes
Bayesian machine learning
Causal Supervised Learning
Computational modelling of soft and complex interfaces
Deep Learning and Mathematical proof checking
Deep learning methods for approximating SPDE
Explainable statistical models
Financial trading and forecasting in energy markets
Foundations of physics informed neural networks
Risk, hedging and control via signatures and ML
Risk, reliability and machine learning
Rogue waves
Statistics and Machine Learning for Assessing Climate Risk
Sustainable and renewable offshore energy
