Panel: Causal ML Research at Microsoft
- Adith Swaminathan, Javier González Hernández, Justin Ding, Daniel McDuff | Microsoft Research
- Microsoft Research Summit 2021 | Causal Machine Learning
Causal machine learning is poised to be the next AI revolution, providing a firm foundation for robust predictions, efficient decisions and human-interpretable explanations. This panel brings together a subset of experts across the Microsoft Research labs to describe their explorations in the frontier of causal ML research. You will learn how MSR approaches explainable AI using causality, how open simulators like CausalCity can accelerate causal discovery, how recommender systems can perform robust counterfactual reasoning, and how important applications in healthcare are enabled by our latest advances in causal ML.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
Causal Machine Learning
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Opening remarks: Causal Machine Learning
- Cheng Zhang
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Research talk: Challenges and opportunities in causal machine learning
- Amit Sharma,
- Cheng Zhang,
- Emre Kiciman
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Research talk: Causal ML and business
- Jacob LaRiviere
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Research talk: Causality for medical image analysis
- Daniel Coelho de Castro
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Research talk: Causal ML and fairness
- Allison Koenecke
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Panel: Causal ML Research at Microsoft
- Adith Swaminathan,
- Javier González Hernández,
- Justin Ding
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Research talk: Post-contextual-bandit inference
- Nathan Kallus
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Demo: Enabling end-to-end causal inference at scale
- Eleanor Dillon,
- Amit Sharma
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Panel: Causal ML at Microsoft
- Juan Lavista Ferres,
- Mingqi Wu,
- Sonia Jaffe
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Panel: Causal ML in industry
- Greg Lewis,
- Ya Xu,
- Totte Harinen
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Closing remarks: Causal Machine Learning
- Emre Kiciman
