Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

arXiv:2607.05393 · astro-ph.IM, astro-ph.GA, astro-ph.HE, cs.AI, cs.LG · Submitted 2026-07-06 · Read on arXiv

Raphaël Bonnet-Guerrini, Bruno Sanchez, Dominique Fouchez, Benjamin Racine, Maya Guy, Mariam Sabalbal, Manal Yassine, Vincenzo Piuri

astro-ph.IM, astro-ph.GA, astro-ph.HE, cs.AI, cs.LG

Submitted: 2026-07-06

Comments: Submitted to Astronomy & Astrophysics, revised after first referee report

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Uncertainty Quantification — 28× in this paper · explained in 8 episodes
Calibration — 23× in this paper · explained in 7 episodes
Accuracy — 11× in this paper · explained in 1 episode
Deep Learning — 10× in this paper
Interpretability — 7× in this paper · explained in 15 episodes
False Positive — 6× in this paper
Latent Space — 6× in this paper · explained in 7 episodes
False Negative — 5× in this paper
Provenance — 5× in this paper · explained in 3 episodes
Adaptation — 4× in this paper · explained in 1 episode
Bayesian Optimization — 3× in this paper · explained in 3 episodes
Difference Image Analysis — 3× in this paper
Embeddings — 3× in this paper · explained in 2 episodes
Latent Representation — 3× in this paper · explained in 2 episodes
Robustness — 3× in this paper · explained in 5 episodes
Transformer — 3× in this paper · explained in 2 episodes
True Positive — 3× in this paper
AUC — 2× in this paper · explained in 2 episodes
Activation Function — 2× in this paper · explained in 1 episode
Aggregation — 2× in this paper · explained in 1 episode
Benchmark — 2× in this paper · explained in 2 episodes
Binary Cross Entropy — 2× in this paper
Domain Shift — 2× in this paper · explained in 4 episodes
Expected Calibration Error — 2× in this paper
Failure Modes — 2× in this paper · explained in 3 episodes
Feature Extraction — 2× in this paper · explained in 2 episodes
Fidelity — 2× in this paper · explained in 2 episodes
Latent Representations — 2× in this paper · explained in 3 episodes
Negative Log-Likelihood — 2× in this paper
Regularization — 2× in this paper · explained in 3 episodes
Signal-to-noise ratio (SNR) — 2× in this paper · explained in 2 episodes
Abstraction — 1× in this paper · explained in 1 episode
Alignment — 1× in this paper · explained in 1 episode
Bayesian Framework — 1× in this paper · explained in 3 episodes
Consistency — 1× in this paper · explained in 3 episodes
Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
Distribution Shift — 1× in this paper · explained in 5 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
Downstream Tasks — 1× in this paper · explained in 2 episodes
Epistemic Uncertainty — 1× in this paper · explained in 9 episodes
Explainable AI (XAI) — 1× in this paper · explained in 7 episodes
Feature Engineering — 1× in this paper · explained in 3 episodes
Hyper Suprime-Cam — 1× in this paper
Initial Data — 1× in this paper · explained in 2 episodes
Monte Carlo dropout — 1× in this paper · explained in 2 episodes
Objective Function — 1× in this paper · explained in 2 episodes

Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

Terminology

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