User profiles for A. Aggelopoulos

Angelos Angelopoulos

- Verified email at phys.uoa.gr - Cited by 4622

Anastasios Nikolas Angelopoulos

- Verified email at berkeley.edu - Cited by 1483

Angelos Angelopoulos

- Verified email at uoa.gr - Cited by 413

Peripheral giant cell granuloma. Clinicopathologic study of 224 new cases and review of 956 reported cases

…, E Kakarantza-Angelopoulou, AP Angelopoulos - International journal of …, 1988 - Elsevier
The clinical and histopathological features of 224 new cases of peripheral giant cell granuloma
were studied. In addition, the data from 956 previously reported cases in the literature …

The use of the buccal fat pad for reconstruction of oral defects: review of the literature and report of 15 cases

…, E Eleftheriadis, AP Angelopoulos - Journal of oral and …, 2000 - Elsevier
Purpose: Although the buccal fat pad (BFP) was originally used as an alternative method for
the closure of small to medium-sized oroantral and oronasal communications, its use has …

[HTML][HTML] Pregnancy-related low back pain

P Katonis, A Kampouroglou, A Aggelopoulos… - Hippokratia, 2011 - ncbi.nlm.nih.gov
Pregnancy related low back pain is a common complaint among pregnant women. It can
potentially have a negative impact on their quality of life. The aim of this article is to present a …

[HTML][HTML] Tackling faults in the industry 4.0 era—a survey of machine-learning solutions and key aspects

A Angelopoulos, ET Michailidis, N Nomikos… - Sensors, 2019 - mdpi.com
The recent advancements in the fields of artificial intelligence (AI) and machine learning (ML)
have affected several research fields, leading to improvements that could not have been …

A gentle introduction to conformal prediction and distribution-free uncertainty quantification

AN Angelopoulos, S Bates - arXiv preprint arXiv:2107.07511, 2021 - arxiv.org
Black-box machine learning models are now routinely used in high-risk settings, like medical
diagnostics, which demand uncertainty quantification to avoid consequential model failures…

Prediction-powered inference

AN Angelopoulos, S Bates, C Fannjiang, MI Jordan… - Science, 2023 - science.org
Prediction-powered inference is a framework for performing valid statistical inference when
an experimental dataset is supplemented with predictions from a machine-learning system. …

Image-to-image regression with distribution-free uncertainty quantification and applications in imaging

AN Angelopoulos, AP Kohli, S Bates… - International …, 2022 - proceedings.mlr.press
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 …

Conformal risk control

AN Angelopoulos, S Bates, A Fisch, L Lei… - arXiv preprint arXiv …, 2022 - arxiv.org
We extend conformal prediction to control the expected value of any monotone loss function.
The algorithm generalizes split conformal prediction together with its coverage guarantee. …

Learn then test: Calibrating predictive algorithms to achieve risk control

AN Angelopoulos, S Bates, EJ Candès… - arXiv preprint arXiv …, 2021 - arxiv.org
We introduce a framework for calibrating machine learning models so that their predictions
satisfy explicit, finite-sample statistical guarantees. Our calibration algorithms work with any …

Conformal prediction under feedback covariate shift for biomolecular design

…, S Bates, AN Angelopoulos… - Proceedings of the …, 2022 - National Acad Sciences
Many applications of machine-learning methods involve an iterative protocol in which data
are collected, a model is trained, and then outputs of that model are used to choose what data …