A Thematic Quarter on Causality

From April to July 2023

Introduction

This thematic quarter aims to underline the interactions between Statistical, Probability Theory, Causal Inference theory, and theoretical computer science methods for causal inference. It will enable researchers, students, and practitioners to explore a rich and cross-disciplinary topic. This thematic quarter will explore topics related to, but not limited to:

• Causal discovery
• Causal learning and control problems
• Theoretical foundation of causal inference
• Causal inference and active learning
• Causal learning in low data regime
• Reinforcement learning
• Causal machine learning
• Causal generative models
• Benchmark for causal discovery and causal reasoning

During this quarter, several colloquia and schools will be organized, and some satellite events will be scheduled.

Important Dates

Spring School on Causality	From March 28th to March 31st, 2023
Opening Session of the Thematic Quarter on Causality	From April 11th, 2023
When Causal Inference meets Statistical Analysis	From April 17th to April 21st, 2023
Fundamental Challenges in Causality	From May 9th to May 12th, 2023
Causality in Practice	From June 12th to June 16th, 2023
Study Week on Causal Inference for Industry	From July 3rd to July 7th, 2023
Tools for Causality	From September 24th to September 29th, 2023

Courses

• Contributions of the causal approach: exploration of concrete use cases

When: 📅 February 14th, 2023 from 2:00 to 6:00 PM, EST
Registration: Here

• Causal Discovery

When: 📅 March 16th, 2023 from 2:00 to 6:00 PM, EST
Registration: Here

Scientific Committee

Organizers

Organized by

With additional support from