Past Editions / 2023
CDSM 2023.
Keynote
Dominik JanzingAmazon Research
November 7, 2023
Day 01 / Online
Policy Learning for Many Outcomes of Interest: Combining Optimal Policy Trees with Multi-objective Bayesian Optimisation
Price Elasticity Estimation using Image and Text Data
Data-Driven Investment Decisions for Venture Capital: A Causal Machine Learning Approach
Overcoming Organizational Challenges for Causal Inference Adoption at Dream11
Implementing Causal AI in Industry: Organisational Challenges and Best Practices
Bridging the Gap Between Predictive Performance and Decision Making: Inverse Probability Weighting for Accuracy Estimation
Leveraging Causal Uplift Modeling for Budget Constrained Benefits Allocation
Not Causal or Descriptive But Some Secret, Other Thing: Entropy as a Criterion for Causal Learning
Engagement Dynamics in mHealth
Dynamic Pricing in B2B Markets
Neuro-Causal Models
Policy Learning under Biased Sample Selection
Evaluating Instrument Validity Using the Principle of Independent Mechanism
Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects
Causally Sound Priors for Binary Experiments
Finding Root Causes via Decomposing Complex Systems into Mechanisms
November 8, 2023
Day 02 / Online
Causally Learning an Optimal Rework Policy
The Perks and Perils of Machine Learning in Business Research
Additive Causal Bandits with Unknown Graph
RCTrep: An R Package for the Validation of Estimates of the Average Treatment Effect
Transportability for Bandits with Data from Different Environments
Identifying Dynamic LATEs with a Static Instrument
When Is Heterogeneity Useless? An Analysis of Targeting Potential in Studies with Multiple Arms
Causal Theories and Structural Data Representations for Improving Out-of-Distribution Classification
Identification and Estimation of Discrete Choice Models with Spillovers Using Partial Network Data
Causal Scoring: A Framework for Effect Estimation, Effect Ordering, and Effect Classification
Fixed Effects and Causal Inference
Poisson Regression Under Heterogeneous Treatment Effects
Causal Reasoning and LLMs: A New Frontier
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal
Can Large Language Models Infer Causation from Correlation?
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task
Experimentation and A/B Testing
From Causal Science to Prescriptive Intelligence
Where a presentation lists one name, only the presenting author is shown; co-authors are not recorded for every year.