TMCF workshop series: Prediction algorithms with a causal interpretation (online event)
Wednesday 06 May 2020
Time: 11:00 - 16:30
Search
Graph theory
Prediction algorithms with a causal interpretation
Monday 10 Feb 2020 - Wednesday 19 Feb 2020
Time: 09:00 - 17:00
Network Science in Financial Services
Friday 06 Dec 2019
Time: 09:30 - 14:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Lecture: Large Scale Structures in Random Graphs
Tuesday 13 Dec 2016
Time: 17:37
Turing Lecture: Industrial and commerical
Wednesday 13 Apr 2016
Time: 13:30 - 17:00
Generational Random Graphs – a “Natural” Model for Heterogeneous Temporal Networks?
Tuesday 11 Apr 2017
Time: 18:37
Projects
Molecular causal networks of hypertension
Using machine learning techniques to investigate causal networks of hypertension at molecular level
Network based recommender systems for public procurement
A novel methodology for community detection and link prediction with applications in public procurement
Causal inference for improved cybersecurity threat detection
Understanding the causal links in the tactics and techniques of cyberattacks
Towards incoherent speech as a predictor of psychosis risk
Investigating whether quantitative markers of speech can detect psychotic disorders and help predict clinical outcomes
Automatic detection of genetic oscillators
Developing data analytics for high-throughput single-cell experimental data to aid better understanding of stem cells
Statistics and the law: Probabilistic modelling of forensic evidence
Using real casework to inform the development of probabilistic methods for evaluating complex forensic evidence
Programmes
Publications and software
Data Study Group Final Report: SenSat
Semantic segmentation of 3D point clouds
Data Study Group team. (2020, June 5). Data Study Group Final Report: SenSat. Zenodo. http://doi.org/10.5281/zenodo.3878499
Motif-Based Spectral Clustering of Weighted Directed Networks
Clustering is an essential technique for network analysis, with applications in a diverse range...
Underwood, W. G., Elliott, A., & Cucuringu, M. (2020). Motif-Based Spectral Clustering of Weighted Directed Networks. arXiv preprint arXiv:2004.01293.
Data Study Group Final Report: PlayerLens
Player pathways: Understanding career paths that deliver success for professional football players and clubs
Data Study Group team. (2019, November 29). Data Study Group Final Report: PlayerLens. Zenodo. http://doi.org/10.5281/zenodo.3558253
Hermitian matrices for clustering directed graphs: insights and applications
Graph clustering is a basic technique in machine learning, and has widespread applications in...
Cucuringu, Mihai, Huan Li, He Sun, and Luca Zanetti. "Hermitian matrices for clustering directed graphs: insights and applications." arXiv preprint arXiv:1908.02096 (2019)
Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping
Consider an unknown smooth function f:[0,1]d→R, and say we are given n noisy mod...
M. Cucuringu, H. Tyagi, "Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping", arXiv:1803.03669 (2018), accepted to Journal of Machine Learning Research (JMLR)
An MBO scheme for clustering and semi-supervised clustering of signed networks
We introduce a principled method for the signed clustering problem, where the goal is...
M. Cucuringu, A. Pizzoferrato, Y. van Gennip, An MBO scheme for clustering and semi-supervised clustering of signed networks, (arXiv) (2019)
Anomaly detection in networks with application to financial transaction networks
This paper is motivated by the task of detecting anomalies in networks of financial...
A. Elliott, M. Cucuringu, M. M. Luaces, P. Reidy, and G. Reinert, Anomaly detection in networks with application to financial transaction networks, (arXiv 1901.00402) (2019)
SPONGE: A generalized eigenproblem for clustering signed networks
We introduce a principled and theoretically sound spectral method for k-way clustering in signed...
Mihai Cucuringu, Peter Davies, Aldo Glielmo, Hemant Tyagi; SPONGE: A generalized eigenproblem for clustering signed networks; Proceedings of Machine Learning Research, PMLR 89:1088-1098, 2019.
On denoising modulo 1 samples of a function
Consider an unknown smooth function $f: [0,1] →\mathbb{R}$, and say we are given $n$...
Mihai Cucuringu, Hemant Tyagi; On denoising modulo 1 samples of a function; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1868-1876, AISTATS 2018
Events
TMCF workshop series: Prediction algorithms with a causal interpretation (online event)
Wednesday 06 May 2020
Time: 11:00 - 16:30
Network Science in Financial Services
Friday 06 Dec 2019
Time: 09:30 - 14:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Generational Random Graphs – a “Natural” Model for Heterogeneous Temporal Networks?
Tuesday 11 Apr 2017
Time: 18:37
Lecture: Large Scale Structures in Random Graphs
Tuesday 13 Dec 2016
Time: 17:37
Turing Lecture: Industrial and commerical
Wednesday 13 Apr 2016
Time: 13:30 - 17:00
Impact stories
Interest groups
Learning the organisational principles of living systems
Can machine learning and artificial intelligence help us to discover and understand biological principles?
Machine learning for radio frequency applications
How do we generate robust, real-time machine learning algorithms with integrated hardware and software for radio frequency applications?
Media in the digital age
What are some of the key opportunities and challenges in the current mediasphere, and how can scientific innovation help?
People
Boyko Vodenicharski
Data Scientist
Tao Wen
Enrichment Student
Shubhr Singh
Enrichment Student
Shazia'Ayn Babul
Enrichment Student
Sanjay Budhdeo
Enrichment Student
Matt De Vries
Enrichment Student
Jack Foster
Enrichment Student
Amin Mekacher
Enrichment Student