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BSMArt 2: simpler and faster parameter space scans
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Fernando Abreu de Souza, Nuno Filipe Castro, Miguel Crispim Romão, Mark D. Goodsell, Farid Ibrahimov, Werner Porod
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Toward decision-aware AI for LSST-scale time-domain astronomy
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C. R. Bom, others
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Two Flavon Froggatt-Nielsen Models with Genetic Algorithms
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Miguel Crispim Romão, Stephen F. King
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Machine Learning insights on the Z3 3HDM with Dark Matter
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Fernando Abreu de Souza, Rafael Boto, Miguel Crispim Romão, Pedro N. de Figueiredo, Jorge C. Romão
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Quantifying vacuum-like jets in heavy-ion collisions: a machine learning study
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Miguel Crispim Romão, João Arruda Gonçalves, Jose Guilherme Milhano
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Sensitivity to new physics phenomena in anomaly detection: A study of untunable hyperparameters
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Fernando Abreu de Souza, Maura Barros, Nuno F. Castro, Miguel Crispim Romão, Céu Neiva, Rute Pedro
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Symbolic Regression and Differentiable Fits in Beyond the Standard Model Physics
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Shehu AbdusSalam, Steven Abel, Deaglan Bartlett, Miguel Crispim Romão
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Anomaly detection to identify transients in LSST time series data
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Miguel Crispim Romão, Djuna Croon, Daniel Godines
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Dark classification matters: searching for primordial black holes with LSST
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Miguel Crispim Romão, Djuna Croon, Benedict Crossey, Daniel Godines
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Exploring scotogenic parameter spaces and mapping uncharted dark matter phenomenology with multi-objective search algorithms
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Fernando Abreu de Souza, Nuno Filipe Castro, Miguel Crispim Romão, Werner Porod
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