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We invite everyone that wants to share results obtained in cosmology or time domain astrophysics using deep neural networks or probabilistic machine learning to submit a contribution for a 20 minutes presentation (15min presentation + 5min questions). For that you need to complete the summary by clicking on the button below.
A poster session will also be organized. The posters will be on board in front of the conference venue from the 21st to the 23rd of May. A lightning talk (2 min) will advertize for your poster.
We welcome in particular contributions that target, or report on, the following non-exhaustive list of topics
• Applications of Bayesian Deep Learning in Cosmology and Time Domain Astrophysics
• Methodology for Model Uncertainty Quantification
• Anomaly and outlier detection
• Probabilistic ML frameworks and methodology
• Use of Bayesian deep learning outside of academia
• Ethical and environmental considerations of large-scale machine learning
Contributions do not necessarily need to be astrophysics-focused. Work on relevant ML methodology, or similar considerations in other scientific fields are welcome.
