* equal contribution

  • A. N. Angelopoulos
Note on Full Conformal Risk Control. 2024.
@article{angelopoulos2023fullrisk,
  title={Note on Full Conformal Risk Control},
  author={Angelopoulos, Anastasios N},
  journal={Online Note.},
  year={2023},
  url={https://people.eecs.berkeley.edu/~angelopoulos/publications/working_papers/full-risk.pdf}
}
							

  • A. N. Angelopoulos*
  • J. C. Duchi*
  • T. Zrnic*
PPI++: Efficient prediction-powered inference. 2023.
@article{angelopoulos2023ppi,
  title={PPI++: Efficient prediction-powered inference},
  author={Angelopoulos, Anastasios N and Duchi, John C and Zrnic, Tijana},
  journal={arXiv preprint arXiv:2311.01453},
  year={2023}
}
							

  • C. T. Ye
  • J. Han
  • K. Liu
  • A. N. Angelopoulos
  • L. Griffith
  • K. Monakhova
  • S. You
Learned, Uncertainty-driven Adaptive Acquisition for Photon-Efficient Multiphoton Microscopy. 2023.
@article{ye2023learned,
  title={Learned, Uncertainty-driven Adaptive Acquisition for Photon-Efficient Multiphoton Microscopy},
  author={Ye, Cassandra Tong and Han, Jiashu and Liu, Kunzan and Angelopoulos, Anastasios and Griffith, Linda and Monakhova, Kristina and You, Sixian},
  journal={arXiv preprint arXiv:2310.16102},
  year={2023}
}
							

  • R. Huang*
  • S. Sharma*
  • A. Loquercio*
  • A. N. Angelopoulos
  • K. Goldberg
  • J. Malik
Conformal Policy Learning for Sensorimotor Control Under Distribution Shifts. 2023.
@article{huang2023conformal,
  title={Conformal Policy Learning for Sensorimotor Control Under Distribution Shifts},
  author={Huang, Huang and Sharma, Satvik and Loquercio, Antonio and Angelopoulos, Anastasios and Goldberg, Ken and Malik, Jitendra},
  journal={arXiv preprint arXiv:2311.01457},
  year={2023}
}
							

  • J. Lekeufack*
  • A. N. Angelopoulos*
  • A. Bajcsy*
  • M. I. Jordan**
  • J. Malik**
Conformal Decision Theory: Safe Autonomous Decisions with Imperfect Predictions. 2023.
@article{lekeufack2023conformal,
  title={Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions},
  author={Lekeufack, Jordan and Angelopoulos, Anastasios N and Bajcsy, Andrea and Jordan, Michael I. and Malik, Jitendra},
  journal={arXiv preprint arXiv:2310.05921},
  year={2023}
}
							

  • A. N. Angelopoulos
  • E. J. Candès
  • R. J. Tibshirani
Conformal PID Control for Time-Series Prediction. NeurIPS 2023.
@article{angelopoulos2023conformal,
  title={Conformal PID Control for Time Series Prediction},
  author={Angelopoulos, Anastasios N and Candes, Emmanuel J and Tibshirani, Ryan J},
  journal={Neural Information Processing Systems},
  year={2023}
}
							

  • T. Ding
  • A. N. Angelopoulos
  • S. Bates
  • M. I. Jordan
  • R. J. Tibshirani
Class-Conditional Conformal Prediction With Many Classes. NeurIPS 2023.
@article{ding2023class,
  title={Class-Conditional Conformal Prediction With Many Classes},
  author={Ding, Tiffany and Angelopoulos, Anastasios N and Bates, Stephen and Jordan, Michael I and Tibshirani, Ryan J},
  journal={Neural Information Processing Systems},
  year={2023}
}
							

  • A. N. Angelopoulos
  • S. Bates
Conformal Prediction: A Gentle Introduction. Foundations and Trends® in Machine Learning. 2023. [FnTML]
@article{MAL-101,
	author = {Anastasios N. Angelopoulos and Stephen Bates},
	doi = {10.1561/2200000101},
	issn = {1935-8237},
	journal = {Foundations and Trends{\textregistered} in Machine Learning},
	number = {4},
	pages = {494-591},
	title = {Conformal Prediction: A Gentle Introduction},
	url = {http://dx.doi.org/10.1561/2200000101},
	volume = {16},
	year = {2023},
	bdsk-url-1 = {http://dx.doi.org/10.1561/2200000101}
}
							

  • A. N. Angelopoulos*
  • S. Bates*
  • C. Fannjiang*
  • M. I. Jordan*
  • T. Zrnic*
Prediction-Powered Inference. Science. 2023.

  • B. S. Einbinder
  • S. Bates
  • A. N. Angelopoulos
  • A. Gendler
  • Y. Romano
Conformal Prediction is Robust to Dispersive Label Noise. COPA 2023.

  • A. N. Angelopoulos
  • S. Bates
  • A. Fisch
  • L. Lei
  • T. Schuster
Conformal Risk Control. 2022.

  • S. Sankaranarayanan
  • A. N. Angelopoulos
  • S. Bates
  • Y. Romano
  • P. Isola
Semantic uncertainty intervals for disentangled latent spaces. NeurIPS 2022.

  • Charles Lu*
  • A. N. Angelopoulos*
  • Stuart Pomerantz
Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets. Conference of the Medical Image Computing and Computer Assisted Intervention Society (MICCAI). 2022.

  • A. N. Angelopoulos*
  • Karl Krauth*
  • Stephen Bates
  • Yixin Wang
  • Michael I. Jordan
Recommendation Systems with Distribution-Free Reliability Guarantees. Alexey Chervonenkis Best Paper Award. COPA 2023.

  • A. P. Kohli*
  • A. N. Angelopoulos*
  • S. You
  • K. Yanny
Linear Revolution-Invariance: Modeling and Deblurring Spatially-Varying Imaging Systems. 2022.

  • A. N. Angelopoulos*
  • A. P. Kohli*
  • S. Bates
  • J. Malik
  • M. I. Jordan
  • T. Alshaabi
  • S. Upadhyahyula
  • Y. Romano
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging. ICML'22 spotlight paper. 2022. [ICML22]

  • C. Fannjiang
  • S. Bates
  • A. N. Angelopoulos
  • J. Listgarten
  • M. I. Jordan
Conformal Prediction for the Design Problem. Proceedings of the National Academy of Sciences. 2022. [PNAS]

  • K. Wang
  • A. N. Angelopoulos
  • A. De Goyeneche
  • A. P. Kohli
  • E. Shimron
  • S. Yu
  • J. Malik
  • M. Lustig
Rigorous Uncertainty Estimation for MRI Reconstruction. Oral at the Conference of the International Society for Magnetic Resonance in Medicine. 2022.

  • M. Werner
  • A. N. Angelopoulos
  • S. Bates
  • M. I. Jordan
Online Active Learning with Dynamic Marginal Gain Thresholding. 2022.

  • 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.
@misc{angelopoulos-gentle,
  title={A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification},
  author={Angelopoulos, Anastasios Nikolas and Bates, Stephen},
  url={https://arxiv.org/abs/2107.07511},
  journal={arXiv:2107.07511},
  year={2021}
}
							

  • A. N. Angelopoulos*
  • S. Bates*
  • T. Zrnic*
  • M. I. Jordan
Private Prediction Sets. Harvard Data Science Review. 2022. [HDSR]
@article{angelopoulos2021private,
  title={Private Prediction Sets},
  author={Angelopoulos, Anastasios N and Bates, Stephen and Zrnic, Tijana and Jordan, Michael I},
  journal={arXiv preprint arXiv:2102.06202},
  year={2021}
}
							

  • A. P. Kohli*
  • A. N. Angelopoulos*
  • S. You
  • L. Waller
Shift-variant deblurring for rotationally symmetric systems. Optical Society of America, Computational Optical Sensing and Imaging, 2021. [COSI]
@article{kohli2021lri,
  title={Shift-variant deblurring for rotationally symmetric systems},
  author={Kohli, Amit and Angelopoulos, Anastasios Nikolas and You, Sixian and Waller, Laura},
  journal={Optical Society of America, Computational Optical Sensing and Imaging},
  year={2021}
}
							

  • S. Bates*
  • A. N. Angelopoulos*
  • L. Lei*
  • J. Malik
  • M. I. Jordan
Distribution-Free, Risk-Controlling Prediction Sets. Journal of the ACM 68 (8). 9/2021. [JACM]
@article{batesrcps,
  title={Distribution-Free, Risk-Controlling Prediction Sets},
  author={Bates, Stephen and Angelopoulos, Anastasios Nikolas and Lei, Lihua and Malik, Jitendra and Jordan, Michael I},
  journal={arXiv preprint arXiv:2101.02703},
  year={2021}
}
							

  • A. N. Angelopoulos*
  • S. Bates*
  • J. Malik
  • M. I. Jordan
Uncertainty Sets for Image Classifiers using Conformal Prediction. ICLR 2021 Spotlight paper. 2021. [ICLR2021]
@article{angelopoulosraps,
  title={Uncertainty Sets for Image Classifiers Using Conformal Prediction},
  author={Angelopoulos, Anastasios Nikolas and Bates, Stephen and Malik, Jitendra and Jordan, Michael I},
  journal={arXiv preprint arXiv:2009.14193},
  year={2020}
}
							

  • A. N. Angelopoulos
  • R. Pathak
  • R. Varma
  • M. I. Jordan
On Identifying and Mitigating Bias in the Estimation of the COVID-19 Case Fatality Rate. Harvard Data Science Review Special Issue COVID-19: Unprecedented Challenges and Chances, 2020. [HDSR]
@article{angelopoulosidentifying,
  title={On Identifying and Mitigating Bias in the Estimation of the COVID-19 Case Fatality Rate},
  author={Angelopoulos, Anastasios Nikolas and Pathak, Reese and Varma, Rohit and Jordan, Michael I},
  journal={Harvard Data Science Review},
  year={2020}
}
			      

  • A. N. Angelopoulos*
  • J. N. P. Martel*
  • A. P. S. Kohli
  • J. Conradt
  • G. Wetzstein
Event-based, near-eye gaze tracking beyond 10,000 Hz. Oral at IEEEVR and special issue of Transactions on Visualization and Computer Graphics. 2021. [IEEE TVCG]
@article{angelopoulos2020event,
  title={Event Based, Near Eye Gaze Tracking Beyond 10,000 Hz},
  author={Angelopoulos, Anastasios Nikolas and Martel, Julien NP and Kohli, Amit PS and Conradt, Jorg and Wetzstein, Gordon},
  journal={arXiv preprint arXiv:2004.03577},
  year={2020}
}
			      

  • R. Konrad
  • A. N. Angelopoulos
  • G. Wetzstein
Gaze-contingent ocular parallax rendering for virtual reality. ACM Transactions on Graphics (+SIGGRAPH), 2020. [ACM TOG]
@article{konrad2020gaze,
  title={Gaze-contingent ocular parallax rendering for virtual reality},
  author={Konrad, Robert and Angelopoulos, Anastasios Nikolas and Wetzstein, Gordon},
  journal={ACM Transactions on Graphics (TOG)},
  volume={39},
  number={2},
  pages={1--12},
  year={2020},
  publisher={ACM New York, NY, USA}
}		      
			      

  • A. N. Angelopoulos
  • H. Ameri
  • D. Mitra
  • M. Humayun
Enhanced depth navigation through augmented reality depth mapping in patients with low vision. Scientific Reports, 2019. [Nature SciRep] [Supp]
@article{angelopoulos2019enhanced,
  title={Enhanced Depth Navigation Through Augmented Reality Depth Mapping in Patients with Low Vision},
  author={Angelopoulos, Anastasios Nikolas and Ameri, Hossein and Mitra, Debbie and Humayun, Mark},
  journal={Scientific reports},
  volume={9},
  number={1},
  pages={1--10},
  year={2019},
  publisher={Nature Publishing Group}
}
			      

  • A. N. Angelopoulos
Patent: Universal Pickup. 2015. [Issued US Patent]
@patent{angelopoulos2015guitar,
  title={Universal Pickup},
  author={Angelopoulos, Anastasios Nikolas},
  date = {2015},
  number={US8993868},
}