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Вміст надано Alex Molak. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Alex Molak або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com

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Manage episode 430207385 series 3526805
Вміст надано Alex Molak. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Alex Molak або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

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Can we say something about YOUR personal treatment effect?
The estimation of individual treatment effects is the Holy Grail of personalized medicine.
It's also extremely difficult.
Yet, Scott is not discouraged from studying this topic.
In fact, he quit a pretty successful business to study it.
In a series of papers, Scott describes how combining experimental and observational data can help us understand individual causal effects.
Although this sounds enigmatic to many, the intuition behind this mechanism is simpler than you might think.
In the episode we discuss:
🔹 What made Scott quit a successful business he founded and study causal inference?
🔹 How a false conviction about his own skills helped him learn? 🔹 What are individual treatment effects?
🔹 Can we really say something about individual treatment effects?
Ready to dive in?
About The Guest
Scott Mueller is a researcher and a PhD candidate in causal modeling at UCLA, supervised by Prof. Judea Pearl. He's a serial entrepreneur and the founder of UCode, a coding school for kids. His current research focuses on the estimation of individual treatment effects and their bounds. He works under the supervision of professor Judea Pearl.
Connect with Scott:
- Scott on Twitter/X
- Scott's webpage
About The Host
Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality.
Connect with Alex:
- Alex on the Internet

Support the show

Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4

  continue reading

Розділи

1. Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com (00:00:00)

2. [Ad] All Business. No Boundaries. The DHL Supply Chain Podcast (00:24:20)

3. (Cont.) Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com (00:24:59)

26 епізодів

Artwork
iconПоширити
 
Manage episode 430207385 series 3526805
Вміст надано Alex Molak. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Alex Molak або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

Send us a text

Can we say something about YOUR personal treatment effect?
The estimation of individual treatment effects is the Holy Grail of personalized medicine.
It's also extremely difficult.
Yet, Scott is not discouraged from studying this topic.
In fact, he quit a pretty successful business to study it.
In a series of papers, Scott describes how combining experimental and observational data can help us understand individual causal effects.
Although this sounds enigmatic to many, the intuition behind this mechanism is simpler than you might think.
In the episode we discuss:
🔹 What made Scott quit a successful business he founded and study causal inference?
🔹 How a false conviction about his own skills helped him learn? 🔹 What are individual treatment effects?
🔹 Can we really say something about individual treatment effects?
Ready to dive in?
About The Guest
Scott Mueller is a researcher and a PhD candidate in causal modeling at UCLA, supervised by Prof. Judea Pearl. He's a serial entrepreneur and the founder of UCode, a coding school for kids. His current research focuses on the estimation of individual treatment effects and their bounds. He works under the supervision of professor Judea Pearl.
Connect with Scott:
- Scott on Twitter/X
- Scott's webpage
About The Host
Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality.
Connect with Alex:
- Alex on the Internet

Support the show

Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4

  continue reading

Розділи

1. Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com (00:00:00)

2. [Ad] All Business. No Boundaries. The DHL Supply Chain Podcast (00:24:20)

3. (Cont.) Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com (00:24:59)

26 епізодів

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