21 citations · 54 across the 13 of their papers we have counts for
13 papers
Annotation-Free One-Shot Imitation Learning for Multi-Step Manipulation Tasks
Vijja Wichitwechkarn, Emlyn Williams, Charles Fox +1
Recent advances in one-shot imitation learning have enabled robots to acquire new manipulation skills from a single human demonstration. While existing methods achieve strong perfo…
Adapting to Change: A Comparison of Continual and Transfer Learning for Modeling Building Thermal Dynamics under Concept Drifts
Fabian Raisch, Max Langtry, Felix Koch +3
Transfer Learning (TL) is currently the most effective approach for modeling building thermal dynamics when only limited data are available. TL uses a pretrained model that is fine…
Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models
Vijja Wichitwechkarn, Charles Fox, Ruchi Choudhary
Foundation models for natural language processing have many coherent definitions of hallucination and methods for its detection and mitigation. However, analogous definitions and m…
The value of hedging against energy storage uncertainties when designing energy parks
Max Langtry, Ruchi Choudhary
Energy storage is needed to match renewable generation to industrial loads in energy parks. However, the future performance of bulk storage technologies is currently highly uncerta…
Quantifying the benefit of load uncertainty reduction for the design of district energy systems under grid constraints using the Value of Information
Max Langtry, Ruchi Choudhary
Load uncertainty must be accounted for during design to ensure building energy systems can meet energy demands during operation. Reducing building load uncertainty allows for impro…
Rationalising data collection for supporting decision making in building energy systems using Value of Information analysis
Max Langtry, Chaoqun Zhuang, Rebecca Ward +5
The use of data collection to support decision making through the reduction of uncertainty is ubiquitous in the management, operation, and design of building energy systems. Howeve…
Impact of data for forecasting on performance of model predictive control in buildings with smart energy storage
Max Langtry, Vijja Wichitwechkarn, Rebecca Ward +5
Data is required to develop forecasting models for use in Model Predictive Control (MPC) schemes in building energy systems. However, data is costly to both collect and exploit. De…
Energy Modelling and Forecasting for an Underground Agricultural Farm using a Higher Order Dynamic Mode Decomposition Approach
Zack Xuereb Conti, Rebecca Ward, Ruchi Choudhary
This paper presents an approach based on higher order dynamic mode decomposition (HODMD) to model, analyse, and forecast energy behaviour in an urban agriculture farm situated in a…
Value of Information Analysis for rationalising information gathering in building energy analysis
Max Langtry, Chaoqun Zhuang, Rebecca Ward +5
The use of monitored data to improve the accuracy of building energy models and operation of energy systems is ubiquitous, with topics such as building monitoring and Digital Twinn…
A physics-based domain adaptation framework for modelling and forecasting building energy systems
Zack Xuereb Conti, Ruchi Choudhary, Luca Magri
State-of-the-art machine-learning-based models are a popular choice for modeling and forecasting energy behavior in buildings because given enough data, they are good at finding sp…
A microsimulation of spatial inequality in energy access: A Bayesian multi-level modelling approach for urban India
A. P. Neto-Bradley, R. Choudhary, P. Challenor
Access to sustained clean cooking in India is essential to addressing the health burden of indoor air pollution from biomass fuels, but spatial inequality in cities can adversely a…
Continuous calibration of a digital twin: comparison of particle filter and Bayesian calibration approaches
Rebecca Ward, Ruchi Choudhary, Alastair Gregory +2
Assimilation of continuously streamed monitored data is an essential component of a digital twin; the assimilated data are used to ensure the digital twin is a true representation…
Slipping through the net: can data science approaches help target clean cooking policy interventions?
André Paul Neto-Bradley, Ruchi Choudhary, Amir Bazaz
Reliance on solid biomass cooking fuels in India has negative health and socio-economic consequences for households, yet policies aimed at promoting uptake of LPG for cooking have…