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Posts
Follow-up to mDAGs—now with selection bias!
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Ryan Carey, Marina Maciel Ansanelli, Elie Wolfe, and Robin Evans have released a paper characterizing the interventional equivalence class of directed acyclic graph models under both marginalization and selection (or conditioning).
Linying Yang releases paper on ‘frengression’
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Linying Yang has released a paper, Frugal, Flexible, Faithful: Causal Data Simulation via Frengression, which uses a generative method for simulating causal datasets. This builds on the frugal parameterization (Evans and Didelez, 2024) in various ways:
New Research Intern
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Paper Accepted to UAI 2025
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Augmented marginal ratio
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Linying Yang has today shared a manuscript on Outcome-informed weighting for robust ATE estimation. The paper, inspired by Taufiq et al., 2023, augments the marginal ratio estimand in that paper in a manner analogous to augmented inverse probability weighting, securing doubly-robust properties.
Power Likelihood Paper Accepted
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Welcome to Jakob Zeitler!
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Paper Accepted to NeurIPS 2024
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Challenges in Categorical Data Analysis
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Robin Evans is the plenary speaker at Challenges in Categorical Data Analysis, a workshop being held at LSE. Linying Yang also attended.
StatML Co-Director
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Frontiers in Statistical Science
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Robin Evans is General Chair of UAI 2024
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Algebraic Economics Workshop
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Robin Evans presented his work on Model Selection and Local Geometry at the IMSI in Chicago.
RSS Discussion Meeting
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Robin Evans and Vanessa Didelez presented their work on Parameterizing and simulating from causal models at the Royal Statistical Society in London. See the video here, and the DeMO with Xi Lin and Daniel Manela here.
Robin Evans Promoted to Professor
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Robin Evans and Xi Lin at FunCausal Workshop
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Program Chair for UAI 2023
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group
publications
talks
Model selection and local geometry
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Social Statistics Seminar
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
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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
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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
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Realistic Simulation from Causal Models
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Binghamton University Statistics Seminar.
Realistic Simulation from Causal Models
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Talk at the Joint Statistical Meetings in Boston, organized by Xinwei Shen.
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 page is from 2024.]
StatML CDT Causal Inference Module
Graduate Course, University of Oxford, Department of Statistics, 2025
Graphical Models
Masters-level course, University of Oxford, Department of Statistics, 2025
This Part C, OMMS and MSc module covers graphical models, exploring their theory and applications in statistical analysis.