Anastasios Angelopoulos

Ph.D. student in Electrical Engineering and Computer Science
at the University of California, Berkeley

Student of Michael I. Jordan and of Jitendra Malik

Research interests

Building out Distribution-Free Statistics, motivated by applications to medicine and computational imaging.

News

November, 2021 I started the International Seminar on Distribution-Free Statistics! Join the mailing list by emailing me.

September, 2021 We posted Learn then Test on ArXiv. It allows control of arbitrary risks using techniques from multiple testing. See the instance segmentation Colab!

August, 2021 Distribution-Free, Risk-Controlling Prediction Sets was accepted to the Journal of the ACM!

July, 2021 A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification has been posted! We are soliciting feedback before arXiv, so please email me with any and all thoughts if you read it.

Selected publications
    • A. N. Angelopoulos
    • S. Bates
    • E. J. Candès
    • M. I. Jordan
    • L. Lei
    Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control. 2021.
    • A. N. Angelopoulos
    • S. Bates
    A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification. 2021.
    • S. Bates*
    • A. N. Angelopoulos*
    • L. Lei*
    • J. Malik
    • M. I. Jordan
    Distribution-Free, Risk-Controlling Prediction Sets. 2021.
    • A. N. Angelopoulos*
    • S. Bates*
    • J. Malik
    • M. I. Jordan
    Uncertainty Sets for Image Classifiers using Conformal Prediction. 2020.