Anastasios N Angelopoulos — accepted AI-conference papers

2024

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Jordan Lekeufack, Anastasios N. Angelopoulos, Andrea Bajcsy, Michael I. Jordan, Jitendra Malik

ICRA 2024poster

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples of such decisions are ubiquitous, from robot planning algorithms that rely on pedestrian predictions, to calibrating autonomous manufacturing to exhibi…

Cited by 33 Source ↗Scholar ↗

2022

Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging

Anastasios N Angelopoulos, Amit Pal Kohli, Stephen Bates, Michael Jordan, Jitendra Malik, Thayer Alshaabi +2

ICML 2022spotlight

Image-to-image regression is an important learning task, used frequently in biological imaging. Current algorithms, however, do not generally offer statistical guarantees that protect against a model’s mistakes and hallucinations. To address this, we develop uncertainty quantification techniques wit…

Cited by 119 Source ↗PDF ↗code ↗Scholar ↗