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Spotlight Presentations
Adrian Weller · Osbert Bastani · Jake Snell · Tal Schuster · Stephen Bates · Zhendong Wang · Margaux Zaffran · Danielle Rasooly · Varun Babbar

Sat Jul 23 11:15 AM -- 12:15 PM (PDT) @
in Workshop on Distribution-Free Uncertainty Quantification »

Probabilistic Conformal Prediction Using Conditional Random Samples by Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou and David Blei

On the Utility of Prediction Sets in Human-AI Teams by Varun Babbar, Umang Bhatt and Adrian Weller

Adaptive Conformal Predictions for Time Series by Margaux Zaffran, Olivier Féron, Yannig Goude, Julie Josse and Aymeric Dieuleveut

Approximate Conditional Coverage via Neural Model Approximations by Allen Schmaltz and Danielle Rasooly

Practical Adversarial Multivalid Conformal Prediction by Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam and Aaron Roth

VaR-Control: Bounding the Probability of High-Loss Predictions by Jake Snell, Thomas Zollo and Richard Zemel

Confident Adaptive Language Modeling by Tal Schuster and Adam Fisch

Author Information

Adrian Weller (University of Cambridge, Alan Turing Institute)
Adrian Weller

Adrian Weller is Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI, and is a Turing AI Fellow leading work on trustworthy Machine Learning (ML). He is a Principal Research Fellow in ML at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he is Programme Director for Trust and Society. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. Previously, Adrian held senior roles in finance. He received a PhD in computer science from Columbia University, and an undergraduate degree in mathematics from Trinity College, Cambridge.

Osbert Bastani (University of Pennsylvania)
Jake Snell (University of Toronto)
Tal Schuster (Google)
Stephen Bates (University of California, Berkeley)
Zhendong Wang (University of Texas at Austin)
Margaux Zaffran (INRIA)
Danielle Rasooly (Harvard University)
Varun Babbar (Cambridge University)

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