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research_publications

Data Study Group Final Report: MRC Clinical Trials Unit, UCL

Monitoring in Clinical Trials: Identifying poor performance at recruitment sites participating in clinical trial research

Data Study Group team. (2022, September 13). Data Study Group Final Report: MRC Clinical Trials Unit, UCL. Zenodo. https://doi.org/10.5281/zenodo.7075637

research_publications

Learning to Guide Online Multi-Contact Receding Horizon Planning

In Receding Horizon Planning (RHP), it is critical that the motion being executed facilitates...

Wang, J., Lembono, T. S., Kim, S., Calinon, S., Vijayakumar, S., & Tonneau, S. (Accepted/In press). Learning to Guide Online Multi-Contact Receding Horizon Planning. In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

research_publications

Tracking abuse on Twitter against football players in the 2021-22 Premier League Season

Online abuse against prominent sportspeople, such as football players, is a growing concern. To...

research_publications

Sparse-Dense Motion Modelling and Tracking for Manipulation without Prior Object Models

This work presents an approach for modelling and tracking previously unseen objects for robotic...

research_publications

RGB-D SLAM in Indoor Planar Environments With Multiple Large Dynamic Objects

This work presents a novel dense RGB-D SLAM approach for dynamic planar environments that...

research_publications

A Versatile Co-Design Approach For Dynamic Legged Robots

We present a versatile framework for the computational co-design of legged robots and dynamic...

research_publications

Common Regulatory Capacity for AI

The use of artificial intelligence (AI) is increasing across all sectors of the economy...

Aitken, M., Leslie, D., Ostmann, F., Pratt, J., Margetts, H., & Dorobantu, C. (2022). Common Regulatory Capacity for AI. The Alan Turing Institute. https://doi.org/10.5281/zenodo.6838946

research_publications

Measuring national mood with music

Using machine learning to construct a measure of national valence from audio data

E. Benetos, A. Ragano, D. Sgroi, and A. Tuckwell, “Measuring National Mood with Music: Using Machine Learning to Construct a Measure of National Valence from Audio Data”, Behavior Research Methods, Feb. 2022. https://doi.org/10.3758/s13428-021-01747-7

research_publications

The Node-wise Pseudo-marginal Method

Motivated by problems from neuroimaging in which existing approaches make use of “mass univariate”...

D. Thesingarajah and A. M. Johansen. The Node-wise Pseudo-marginal Method. Statistics and Computing, 32(43) 1-31: 2022.

research_publications

Product-form estimators

Exploiting independence to scale up Monte Carlo

J. Kuntz, F. R. Crucinio, and A. M. Johansen. Product-form estimators: exploiting independence to scale up Monte Carlo. Statistics and Computing, 32(12):1–22, 2022.

research_publications

Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap

Simulator-based models are models for which the likelihood is intractable but simulation of synthetic...

Dellaporta H., Knoblauch J., Damoulas T., Briol, F-X. (2022). Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap. arXiv:2202.04744.

research_publications

Dynamic causal Bayesian optimization

This paper studies the problem of performing a sequence of optimal interventions in a...

Aglietti V., Dhir N., Gonzalez J., Damoulas T., (2021). Dynamic causal Bayesian optimization. arXiv:2110.13891.

research_publications

Spatio-temporal variational Gaussian processes

We introduce a scalable approach to Gaussian process inference that combines spatio-temporal filtering with...

Hamelijnck O., Wilkinson W. J, Loppi N. A., Solin A., Damoulas T (2021). Spatio-Temporal Variational Gaussian Processes. arXiv:2111.01732v1.

research_publications

Higher order kernel mean embeddings to capture filtrations of stochastic processes

Stochastic processes are random variables with values in some space of paths. However, reducing...

Salvi C., Lemercier M., Liu C., Horvath B., Damoulas T., Lyons T. Higher order kernel mean embeddings to capture filtrations of stochastic processes. arXiv:1910.03906.

research_publications

SigGPDE: Scaling sparse Gaussian processes on sequential data

Making predictions and quantifying their uncertainty when the input data is sequential is a...

Lemercier M., Salvi C., Cass T., Bonilla E. V., Damoulas T., Lyons T. (2021). SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. arXiv:2105.04211.

research_publications

Probabilistic sequential matrix factorization

We introduce the probabilistic sequential matrix factorization (PSMF) method for factorizing time-varying and non-stationary...

Akyildiz, Ö. D., van den Burg, G.J.J., Damoulas, T., Steel, M.F.J. (2021). Probabilistic sequential matrix factorization. arXiv:1910.03906.

research_publications

AI UK

The Turing Lectures

Impact

The Turing Podcast

Equality, diversity and inclusion

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Simulating energy efficiency opportunities for households

Premdeep Gill

Erin Young

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Turing TIN Data Study Group – February 2023

Data Study Groups

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Join our mailing lists

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AI UK

The Turing Lectures

Impact

The Turing Podcast

Equality, diversity and inclusion

Simulating energy efficiency opportunities for households

Premdeep Gill

Erin Young

Enrichment scheme

Turing TIN Data Study Group – February 2023

Data Study Groups

Partnering with the Turing

Join our mailing lists

Press office