42 citations · 82 across the 9 of their papers we have counts for
9 papers
RangL: A Reinforcement Learning Competition Platform
Viktor Zobernig, Richard A. Saldanha, Jinke He +12
The RangL project hosted by The Alan Turing Institute aims to encourage the wider uptake of reinforcement learning by supporting competitions relating to real-world dynamic decisio…
Rule-based Evolutionary Bayesian Learning
Themistoklis Botsas, Lachlan R. Mason, Omar K. Matar +1
In our previous work, we introduced the rule-based Bayesian Regression, a methodology that leverages two concepts: (i) Bayesian inference, for the general framework and uncertainty…
Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities
Indranil Pan, Lachlan Mason, Omar Matar
Recent advances in machine learning, coupled with low-cost computation, availability of cheap streaming sensors, data storage and cloud technologies, has led to widespread multi-di…
Multiphase flow applications of non-intrusive reduced-order models with Gaussian process emulation
Themistoklis Botsas, Indranil Pan, Lachlan R. Mason +1
Reduced-order models (ROMs) are computationally inexpensive simplifications of high-fidelity complex ones. Such models can be found in computational fluid dynamics where they can b…
Numerical simulation, clustering and prediction of multi-component polymer precipitation
Pavan Inguva, Lachlan Mason, Indranil Pan +2
Multi-component polymer systems are of interest in organic photovoltaic and drug delivery applications, among others where diverse morphologies influence performance. An improved u…
Rule-based Bayesian regression
Themistoklis Botsas, Lachlan R. Mason, Indranil Pan
We introduce a novel rule-based approach for handling regression problems. The new methodology carries elements from two frameworks: (i) it provides information about the uncertain…
Single-Bubble Dynamics in Nanopores: Transition Between Homogeneous and Heterogeneous Nucleation
Soumyadeep Paul, Wei-Lun Hsu, Mirco Magnini +4
When applying a voltage bias across a thin nanopore, localized Joule heating can lead to single bubble nucleation, offering a unique platform for studying nanoscale bubble behavior…
Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation
Romit Maulik, Themistoklis Botsas, Nesar Ramachandra +2
Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerg…
Data-driven surrogate modelling and benchmarking for process equipment
Gabriel F. N. Gonçalves, Assen Batchvarov, Yuyi Liu +4
In chemical process engineering, surrogate models of complex systems are often necessary for tasks of domain exploration, sensitivity analysis of the design parameters, and optimiz…