Online Causal Inference Seminar

A regular online international causal inference seminar.

Jakob Runge: Causal Inference on Time Series Data with the Tigramite Package
Jakob Runge: Causal Inference on Time Series Data with the Tigramite Package
Joseph Antonelli: Partial identification & unmeasured confounding with multiple treatment & outcomes
Joseph Antonelli: Partial identification & unmeasured confounding with multiple treatment & outcomes
Sizhu Lu: Estimating treatment effects with competing intercurrent events in randomized trials
Sizhu Lu: Estimating treatment effects with competing intercurrent events in randomized trials
Jiaqi Zhang: Learning causal cellular programs from large-scale perturbations
Jiaqi Zhang: Learning causal cellular programs from large-scale perturbations
Julie Josse: Causal Alternatives to Meta-Analysis
Julie Josse: Causal Alternatives to Meta-Analysis
Matias Cattaneo: Estimation and Inference in Boundary Discontinuity Designs
Matias Cattaneo: Estimation and Inference in Boundary Discontinuity Designs
Francesco Locatello: Powering causality with ML: Discovery, Representations, and Inference
Francesco Locatello: Powering causality with ML: Discovery, Representations, and Inference
Luke Keele: Clustered Observational Studies: A Review of Concepts and Methods
Luke Keele: Clustered Observational Studies: A Review of Concepts and Methods
Sam Pimentel: Design Sensitivity and Its Implications for Weighted Observational Studies
Sam Pimentel: Design Sensitivity and Its Implications for Weighted Observational Studies
Zijian Guo: Multi-Source Learning with Minimax Optimization: Adversarial Robustness to Invariance
Zijian Guo: Multi-Source Learning with Minimax Optimization: Adversarial Robustness to Invariance
Angela Zhou: Robust Fitted-Q-Evaluation & Iteration under Sequentially Exogenous Unobsvd Confounders
Angela Zhou: Robust Fitted-Q-Evaluation & Iteration under Sequentially Exogenous Unobsvd Confounders
Young researchers' seminar: Drago Plečko and Daiqi Gao
Young researchers' seminar: Drago Plečko and Daiqi Gao
[SCI+OCIS] Roundtable Panel – Exploring Career Paths in Pharma, Government, and Technology
[SCI+OCIS] Roundtable Panel – Exploring Career Paths in Pharma, Government, and Technology
Nathan Kallus: Learning Surrogate Indices from Historical A/Bs Adversarial ML for Debiased Inference
Nathan Kallus: Learning Surrogate Indices from Historical A/Bs Adversarial ML for Debiased Inference
Dylan Small: Exploration, Confirmation, and Replication in the Same Observational Study
Dylan Small: Exploration, Confirmation, and Replication in the Same Observational Study
Guido Imbens: Identification of nonparametric factor models for average treatment effects
Guido Imbens: Identification of nonparametric factor models for average treatment effects
Alberto Abadie: Synthetic Controls for Experimental Design
Alberto Abadie: Synthetic Controls for Experimental Design
Katherine A. Keith: Proximal Causal Inference with Text Data
Katherine A. Keith: Proximal Causal Inference with Text Data
[SCI+OCIS] Elizabeth A. Stuart: Lessons in
[SCI+OCIS] Elizabeth A. Stuart: Lessons in "causality" from National Academies consensus panels
Vasilis Syrgkanis: Detecting clinician implicit biases in diagnoses using proximal causal inference
Vasilis Syrgkanis: Detecting clinician implicit biases in diagnoses using proximal causal inference
David Bruns-Smith: Augmented balancing weights as linear regression
David Bruns-Smith: Augmented balancing weights as linear regression
Julius von Kügelgen: Multi-Domain Causal Representation Learning
Julius von Kügelgen: Multi-Domain Causal Representation Learning
Eric Tchetgen Tchetgen: Revisiting Identification in the Binary IV Model: the NATE and Beyond
Eric Tchetgen Tchetgen: Revisiting Identification in the Binary IV Model: the NATE and Beyond
Corwin Zigler: Causal health impacts of power plant emission controls ...
Corwin Zigler: Causal health impacts of power plant emission controls ...
Michal Kolesár: Evaluating Counterfactual Policies Using Instruments
Michal Kolesár: Evaluating Counterfactual Policies Using Instruments
Anne Helby Petersen: Two perspectives on interpretable evaluation of causal discovery algorithms
Anne Helby Petersen: Two perspectives on interpretable evaluation of causal discovery algorithms
Davide Viviano: Program Evaluation with Remotely Sensed Outcomes
Davide Viviano: Program Evaluation with Remotely Sensed Outcomes
Qingyuan Zhao: On statistical and causal models associated with acyclic directed mixed graphs (ADMG)
Qingyuan Zhao: On statistical and causal models associated with acyclic directed mixed graphs (ADMG)
Panos Toulis & W. Guo: ML-assisted Randomization Tests for Complex Treatment Effects in A/B Expts
Panos Toulis & W. Guo: ML-assisted Randomization Tests for Complex Treatment Effects in A/B Expts
Yiqing Xu: Factorial Difference-in-Differences
Yiqing Xu: Factorial Difference-in-Differences