Media Summary: Ph.D. student Jonathan Crabbé explains the importance of machine learning While understanding and trusting models and their results is a hallmark of good (data) science, model In this short introductory presentation Mihaela van der Schaar outlines the lab's ongoing vision and research focus, shares some ...

2021 Open House Ml Interpretability - Detailed Analysis & Overview

Ph.D. student Jonathan Crabbé explains the importance of machine learning While understanding and trusting models and their results is a hallmark of good (data) science, model In this short introductory presentation Mihaela van der Schaar outlines the lab's ongoing vision and research focus, shares some ... How can we explain how deep neural networks arrive at decisions? Feature representation is complex and to the human eye ... Research engineer Bogdan Cebere presents Adjutorium, the van der Schaar Lab's cutting-edge automated machine learning ... Postdoc Fergus Imrie introduces key problems surrounding the use of genomics data, starting with the lack of labeled data and the ...

I envision a system that enables successful collaborations between humans and machine learning models by harnessing the ... This meetup was held in Mountain View on November 1, 2017. To view the slides, please visit here: ... This meetup was recorded in New York City on September 10th, 2018. Slides from the meetup can be found here: ... What's happening inside an AI model as it thinks? Why are AI models sycophantic, and why do they hallucinate? Are AI models ...

Photo Gallery

2021 open house - ML interpretability (Jonathan Crabbé)
Interpretable Machine Learning
Open House 2022
2021 open house - introduction (Mihaela van der Schaar)
Model Interpretability in Machine Learning [Google ML Summit]
2021 open house - Adjutorium (Bogdan Cebere)
Interpretable vs Explainable Machine Learning
A Roadmap for the Rigorous Science of Interpretability | Finale Doshi-Velez | Talks at Google
2021 open house - self-supervised learning for genomics (Fergus Imrie)
Interactive and Interpretable Machine Learning Models for Human Machine Collaboration
Ideas on Machine Learning Interpretability
Interpretable Machine Learning Meetup
View Detailed Profile
2021 open house - ML interpretability (Jonathan Crabbé)

2021 open house - ML interpretability (Jonathan Crabbé)

Ph.D. student Jonathan Crabbé explains the importance of machine learning

Interpretable Machine Learning

Interpretable Machine Learning

While understanding and trusting models and their results is a hallmark of good (data) science, model

Open House 2022

Open House 2022

The van der Schaar Lab's 2022

2021 open house - introduction (Mihaela van der Schaar)

2021 open house - introduction (Mihaela van der Schaar)

In this short introductory presentation Mihaela van der Schaar outlines the lab's ongoing vision and research focus, shares some ...

Model Interpretability in Machine Learning [Google ML Summit]

Model Interpretability in Machine Learning [Google ML Summit]

How can we explain how deep neural networks arrive at decisions? Feature representation is complex and to the human eye ...

2021 open house - Adjutorium (Bogdan Cebere)

2021 open house - Adjutorium (Bogdan Cebere)

Research engineer Bogdan Cebere presents Adjutorium, the van der Schaar Lab's cutting-edge automated machine learning ...

Interpretable vs Explainable Machine Learning

Interpretable vs Explainable Machine Learning

Interpretable

A Roadmap for the Rigorous Science of Interpretability | Finale Doshi-Velez | Talks at Google

A Roadmap for the Rigorous Science of Interpretability | Finale Doshi-Velez | Talks at Google

With a growing interest in

2021 open house - self-supervised learning for genomics (Fergus Imrie)

2021 open house - self-supervised learning for genomics (Fergus Imrie)

Postdoc Fergus Imrie introduces key problems surrounding the use of genomics data, starting with the lack of labeled data and the ...

Interactive and Interpretable Machine Learning Models for Human Machine Collaboration

Interactive and Interpretable Machine Learning Models for Human Machine Collaboration

I envision a system that enables successful collaborations between humans and machine learning models by harnessing the ...

Ideas on Machine Learning Interpretability

Ideas on Machine Learning Interpretability

This meetup was held in Mountain View on November 1, 2017. To view the slides, please visit here: ...

Interpretable Machine Learning Meetup

Interpretable Machine Learning Meetup

This meetup was recorded in New York City on September 10th, 2018. Slides from the meetup can be found here: ...

Interpretability: Understanding how AI models think

Interpretability: Understanding how AI models think

What's happening inside an AI model as it thinks? Why are AI models sycophantic, and why do they hallucinate? Are AI models ...