Summary of Position: Bayesian Deep Learning Is Needed in the Age Of Large-scale Ai, by Theodore Papamarkou et al.
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
by Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
First submitted to arxiv on: 1 Feb 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Machine Learning (stat.ML)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper argues that deep learning research has been too focused on achieving high predictive accuracy in tasks involving large image and language datasets. Instead, it highlights the importance of considering other metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data. The authors propose Bayesian deep learning (BDL) as a promising approach that can elevate the capabilities of deep learning, discussing its strengths, challenges, and potential research avenues to address these obstacles. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this paper, researchers discuss how deep learning models are only good at doing what they were trained for. They think that by using something called Bayesian deep learning (BDL), we can make our models better at things like uncertainty, learning new things, and working with science data. The authors say BDL is important because it lets us do more than just predict things correctly. |
Keywords
* Artificial intelligence * Continual learning * Deep learning
