ΑΙhub.org
Watch the invited talks (and much more) from #NeurIPS2019
Couldn’t make it to NeurIPS this week in Vancouver? Or simply unable to make your way to every exciting talk through the maze of 16k participants? Luckily, many of the sessions are available online.
To get started, we’ve embedded the invited talks below.
How To Know – Celeste Kidd
Veridical Data Science – Bin Yu
Machine learning meets single-cell biology: insights and challenges – Dana Pe’er
Social Intelligence – Blaise Aguera y Arcas
From System 1 Deep Learning to System 2 Deep Learning – Yoshua Bengio
Agency + Automation: Designing Artificial Intelligence into Interactive Systems – Jeff Heer
We’ll be featuring paper awards in a future post, so stay tuned.
Did you want us to feature your research? Send me an email with your blog post.
tags: NeurIPS
Sabine Hauert
is Associate Professor at the University of Bristol, and Executive Trustee of AIhub.org
Sabine Hauert
is Associate Professor at the University of Bristol, and Executive Trustee of AIhub.org
AIhub is supported by:
Related posts :
PeSTo: an AI tool for predicting protein interactions
The model can predict the binding interfaces of proteins when they bind other proteins, nucleic acids, lipids, ions, and small molecules.
01 June 2023, by
EPFL
Tetris reveals how people respond to an unfair AI algorithm
An experiment in which two people play a modified version of Tetris revealed that players who get fewer turns perceive the other player as less likeable, regardless of whether a person or an algorithm allocates the turns.
31 May 2023, by
Cornell University
AIhub monthly digest: May 2023 – mitigating biases, ICLR invited talks, and Eurovision fun
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
30 May 2023, by
Lucy Smith
Latest AI announcements from the US Government include updated strategic plan
Find out more about the latest initiatives pertaining to responsible AI in the USA.
26 May 2023, by
Lucy Smith
Interview with Haotian Xue: learning intuitive physics from videos
A framework for learning 3D-grounded visual intuitive physics models from videos of complex scenes.
25 May 2023, by
AIhub Editor
Using engineered bacteria and AI to sense and record environmental signals
Synthetic biologists engineer bacterial swarm patterns to visibly record environment and use deep learning to decode patterns.
24 May 2023, by
Columbia University in the City of New York