Model selection and local geometry
Published:
Social Statistics Seminar
Posts by Collection
group
publications
talks
Oberwolfach Workshop
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Workshop on Algebraic Statistics
Kcl Seminar
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Statistics Seminar
Quantum Workshop
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Workshop on Quantum networks
Siam Declined
Published:
SIAM Applied Algebraic Geometry (declined for family reasons)
Rss Conference
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Causal Inference Session, RSS Conference
Cm Statistics
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CM Statistics
Glasgow Seminar
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Statistics Seminar
Warwick Seminar
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CRiSM Seminar
Crm Workshop
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Workshop on Causal inference for complex graphical structures
Jsm Session
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Algebraic Statistics Session, JSM
Uai Workshop
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UAI Causal Workshop
Tu Munich Workshop
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Graphical Models: Conditional Independence and Algebraic Structures
Aim Square
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AIM SQuaRE on Nested Models
Karolinska Seminar
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Seminar at Karolinska Institute
Mrc Seminar
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Seminar at MRC Biostatistics Unit
Uai Discussion
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Discussion of Varando and Hansen’s ‘Graphical continuous Lyapunov models’
Isi Virtual
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Virtual ISI Conference
Oxml School
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OxML Summer School: Introduction to Causality for Machine Learning
Pacific Causal
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Pacific Causal Inference Conference
Oxford Workshop
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NovoNordisk JICI Workshop
Online Discussant
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Discussant of Foygel et al. (2022)
Inequality-free mDAGs
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Quantum Physics and Statistical Causal Models Workshop
Ams Virtual
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AMS Western Sectional Meeting
Epfl Seminar
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EPFL Statistics Seminar
Ims London
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IMS Meeting
Parameterizing and simulating from causal models
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Copenhagen Biostatistics Seminar
Many Data: Combining observational and experimental data
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NovoNordisk JICI Workshop
Oberwolfach Workshop
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Workshop on Algebraic Structures in Statistical Methodology
Cambridge Seminar
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Statistical Laboratory Seminar
Online Discussant
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Discussant of Dang et al. (2022)
Parameterizing and simulating from causal models
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UPF Statistics Seminar
Parameterizing and simulating from causal models
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Computational Statistics and Machine Learning Seminar
Towards standard imsets for maximal ancestral graphs
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Workshop on Causal Inference and Quantum Foundations, talk is here.
Combining Observational and Experimental Data
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Plenary talk at Workshop on Fundamental Challenges in Causality
Many Data: Combining Observational and Experimental Data
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Oxford-Danish Symposium
Towards Standard Imsets for Maximal Ancestral Graphs
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Miniworkshop on Graphical Models and Causality
Parameterizing and Simulating from Causal Models
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Algorithms and Computationally Intensive Inference Seminar
Model selection and local geometry
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Plenary talk at Workshop on Algebraic Economics
Parameterizing and Simulating from Causal Models
Published:
Statistics Seminar, King’s College London
Linkage as Data Fusion
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JICI Meeting
Marginal Log-Linear Parameters: Lessons for the Continuous Case
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Keynote Talk at Challenges in Categorical Data Analysis Workshop.
Many Data
Published:
teaching
MSc R Programming
Postgraduate course, University of Oxford, Department of Statistics, 2014
Course Material
Part A Statistical Programming
Undergraduate course, University of Oxford, Department of Statistics, 2021
This module introduces fundamental concepts and practices in statistical programming, essential for data analysis. See the Canvas page for more details.
APTS Causal Inference Module
Graduate Course, University of Oxford, Department of Statistics, 2024
This module focuses on causal inference, covering methods for establishing cause-and-effect relationships from data.
Graphical Models
Masters-level course, University of Oxford, Department of Statistics, 2024
This Part C, OMMS and MSc module covers graphical models, exploring their theory and applications in statistical analysis.
StatML CDT Causal Inference Module
Graduate Course, University of Oxford, Department of Statistics, 2025