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16:00
Poster Lightning Talks
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16:30
Machine Learning for Calorimetry Physics: Classification and Anomaly Detection
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Bjartur í Túni Mortensen
(Niels Bohr Institute, Copenhagen University)
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16:30
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming
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Yongquan Qu
(Columbia University)
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16:30
ML in the Dating of Greenland Ice Cores: A GRU Method for Automated Annual Layer Identification
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Rasmus Arentoft Nielsen
(Physics of Ice, Climate and Earth (PICE) - NBI)
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16:30
Geomagnetic Forecasting with Neural Networks
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Ali Ahmad
Florent Imishti Mustafaj
(University of Copenhagen)
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16:30
Exploring transport in coupled quantum dots for quantum reservoir computing
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Alva Höglund
(Lund University)
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16:30
Data-driven modelling for limited area forecasting
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Leif Denby
(Danish Meteorological Institute)
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16:30
MetalAI - Atomic structure calculations guided by machine learning
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Moust Holmes
(University of Copenhagen)
Rasmus Damgaard Nielsen
(DAWN, NBI, Copenhagen University)
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16:30
Predicting Glacier Thickness: A Machine Learning Approach
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Josephine Kande
(Copenhagen University, Niels Bohr Institute)
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16:30
Data-driven Methods for Mitigating Stellar Variability in Sun-as-a-Star Observations
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Jinglin Zhao
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16:30
Investigating noise patterns in the JWST/MIRI detector with ML techniques
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Prune August
(DTU Space)
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16:30
Simulated analogues: a new methodology for non-parametric matching of models to observations
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Mikkel Christensen
(Niels Bohr Institute)
Rajika Kuruwita
(Heidelberg Institute for Theoretical Studies)
Rami Al-Belmpeisi
(DTU)
Troels Haugbølle
(Niels Bohr Institute)
Vito Tuhtan
(Niels Bohr Institute)
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16:30
Model-independent anomaly detection in gravitational waves
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Emilie Hertig
(University of Cambridge)
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16:30
A local diagnostic program for unitary evolution in general space-times
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Ka Hei Choi
(Ludwig Maximilian University of Munich)
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16:30
Deep Learning Assisted Raman Spectroscopy for Rapid Identification of 2D Materials
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Yaping Qi
(Tohoku University)
