Schedule
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Tuesday |
Wednesday |
Thursday |
Friday |
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10:00 – 11:30 |
Matthew Mould Astrophysics-agnostic inference of gravitational-wave populations with Bayesian normalizing flows |
Justin Janquart Normalizing flows as an avenue to study overlapping gravitational wave signals |
Ann-Kristin Malz Providing Uncertainty Estimates with Conformal Prediction |
Alex Kolmus Tuning neural posterior estimation for gravitational waves |
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Joe Bayley Reconstructing mass dynamics from gravitational waves |
Thibeau Wouters Accelerating parameter estimation of binary neutron star mergers with normalizing flows |
Stephen Green Advances in Gravitational Wave Inference using Deep Learning |
Costantino Pacilio Likelihood-free inference of ringdown gravitational waves in the time domain |
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Nihar Gupte Strong signs of eccentricity in the population of gravitational-wave signals from binary black holes: insights from DINGO |
Chayan Chatterjee Decoding the Cosmic Orchestra: Reconstruction of Binary Black Hole Harmonics in LIGO using Deep Learning |
David Keitel Opening up new discovery spaces with machine learning: Long-duration transient gravitational waves |
Matteo Scialpi Physics-Informed Neural Networks for gravitational wave sources' parameter estimation |
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Rhona McTeague Application of physics informed neural networks for the solution of the Tolman–Oppenheimer–Volkoff equation |
Michael Williams Importance nested sampling with normalizing flows gravitational-wave inference |
Discussions (finish at 12:00) |
Maximilian Dax Rapid characterization of binary neutron star mergers with machine learning |
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11:30 – 13:00 |
Discussions |
Discussions |
Discussions |
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13:00 – 14:30 |
Lunch By Woolies of Brodick |
Lunch By Woolies of Brodick |
Free time |
Lunch By Woolies of Brodick |
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14:30 – 15:30 |
Prasanna Mohan Joshi A novel neural-network architecture for continuous-wave all-sky searches |
Alexandre S. Göttel Evidence networks as waveform systematic control |
Discussions |
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Przemysław Figura Denoising Diffusion Probabilistic Models used in search for continuous gravitational waves |
Matteo Boschini Extending black-hole remnant surrogate models to extreme mass ratios |
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Rodrigo Tenorio Kaggle competition to detect continuous gravitational-wave signals |
Swetha Bhagwat Modelling amplitudes in precessing binary black holes ringdown using Gaussian process regression |
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Vasileios Skliris Using machine learning to detect unmodelled GW signals - MLy-Pipeline |
Patricia Schmidt |
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15:30 – 17:00 |
Discussions |
Discussions |
Discussions |
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17:30 – 19:30 |
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Networking Dinner Auchrannie Resort |
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