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Causality_hi-res logo

Causality Reunion

Program
Causality
Location

Calvin Lab Auditorium

Date
Monday, May 8 – Thursday, May 11, 2023
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  • Schedule

9 – 9:25 a.m.
Coffee and Check-in
9:25 – 9:30 a.m.
Opening Remarks
9:30 – 10:30 a.m.
A Cautious Approach To Constraint-Based Causal Model Selection Based on Equivalence Tests

Daniel Malinsky (Columbia University)
10:30 – 11 a.m.
Break
11 a.m. – 12 p.m.
Empirical Gateaux Derivatives for Causal Inference and Optimization-Based Estimators

Angela Zhou (USC)
12 – 2 p.m.
Lunch
2 – 3 p.m.
Causal Inference in Cluster DAGs

Jin Tian (Iowa State University)
3 – 3:30 p.m.
Break
3:30 – 4:15 p.m.
Identifiability of Statistical Models with Latent Symmetries

Leonard Schulman (Caltech)
4:15 – 5 p.m.
Statistical Inference from Networked Data

Constantinos Daskalakis (Massachusetts Institute of Technology)
5 – 6 p.m.
Reception
9 – 9:30 a.m.
Coffee and Check-in
9:30 – 10:30 a.m.
Why DAGs are Inappropriate for Causal Reasoning in Complex Systems

Johannes Textor (Radboud University Nijmegen, The Netherlands)
10:30 – 11 a.m.
Break
11 a.m. – 12 p.m.
Generalizing Conditional Independence: Nested Markov Models

Thomas Richardson (University of Washington)
12 – 2 p.m.
Lunch
2 – 3 p.m.
Stable Discovery of Interpretable Subgroups via Calibration in Causal Studies

Bin Yu (UC Berkeley)
3 – 3:30 p.m.
Break
3:30 – 5 p.m.
Causality & LLMs Discussion
9 – 9:30 a.m.
Coffee and Check-in
9:30 – 10:30 a.m.
Confounding and Dependence in Spatial Statistics

Betsy Ogburn (John Hopkins)
10:30 – 11 a.m.
Break
11 a.m. – 12 p.m.
Optimal Neighbourhood Selection in Structural Equation Models

Bryon Aragam (University of Chicago)
12 – 2 p.m.
Lunch
2 – 3 p.m.
Open Problem Session
3 – 3:30 p.m.
Break
3:30 – 4:15 p.m.
Target Trials and Structural Nested Models: Emulating RCTs using Observational Longitudinal Data: Recent Theoretical Empirical Results and Increasing Role in Clinical Medicine

James Robins (Harvard University)
4:15 – 5 p.m.
Augmented Balancing Weights as Linear Regression

David Bruns-Smith (UC Berkeley)
9 – 9:30 a.m.
Coffee and Check-in
9:30 – 10:30 a.m.
Causal Discovery Under Limited Global Confounding

Bijan Mazaheri (Caltech)
10:30 – 11 a.m.
Break
11 – 11:45 a.m.
Active Causal Structure Learning with Advice

Arnab Bhattacharyya (National University of Singapore)
11:45 a.m. – 12:30 p.m.
On Measuring Causal Contributions via Do-Interventions

Shiva Kasiviswanathan (Amazon)
12:30 – 2 p.m.
Lunch
2 – 3 p.m.
A New Design-Based Framework for Randomized Experiments and the Riesz Estimator

Christopher Harshaw (UC Berkeley)
3 – 3:30 p.m.
Break
3:30 – 5 p.m.
Discussion with Issa Kohler-Hausmann and Lily Hu
3:30 – 5 p.m.
Neglected Assumptions in Causal Inference and Their Implications for the Quantitative Study of Bias and Discrimination

Issa Kohler-Hausmann (Yale Law School),
Lily Hu (Yale University),
Betsy Ogburn (John Hopkins)
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    • Algorithms, Society, and the Law
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    • Staff
    • Current Long-Term Visitors
    • Research Fellows
    • Postdoctoral Researchers
    • Scientific Advisory Board
    • Governance Board
    • Industry Advisory Council
    • Affiliated Faculty
    • Science Communicators in Residence
    • Law and Society Fellows
  • Participate
    • Apply to Participate
    • Plan Your Visit
    • Location & Directions
    • Postdoctoral Research Fellowships
    • Law and Society Fellowships
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    • Industrial Partnerships
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