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Week Mon. 18 Tue. 19 Wed. 20 Thu. 21 Fri. 22 List

	Mon. 18	Tue. 19	Wed. 20	Thu. 21	Fri. 22
08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00	In person Registration 8:45 - 9:45 (1h) In person Registration Registration of in person participants Welcome speech 9:45 - 10:00 (15min) Welcome speech Henri Mineur amphitheater / Plenary online session Organizers Review 10:00 - 11:00 (1h) Review Henri Mineur amphitheater / Plenary online session › Review on cosmology and machine learning - Benjamin Wandelt, Institut d'Astrophysique de Paris 10:00-11:00 (1h) Break 11:00 - 11:20 (20min) Break Breakout rooms Contributed 11:20 - 12:20 (1h) Contributed Henri Mineur amphitheater / Plenary online session › Probabilistic Mapping of Dark Matter by Neural Score Matching - Benjamin Remy, Cosmostat, AIM, IRFU, CEA-Saclay 11:20-11:35 (15min) › Simulation and Segmentation with Deep Learning for Euclid - Hubert Bretonnière, Institut d'astrophysique spatiale 11:35-11:50 (15min) › Search for galaxy-scale strong lenses in DES and CFIS - Frédéric Courbin, EPFL, Laboratoire d'astrophysique, Ecole Polytechnique Fed ´ erale de Lausanne 11:50-12:05 (15min) › Learning from 3D tomographic 21cm maps - Caroline Heneka, Hamburg Observatory, Hamburg University 12:05-12:20 (15min) Flash talk 15:00 - 15:20 (20min) Flash talk Henri Mineur amphitheater / Plenary online session › Unifying large-scale spectroscopy, astrometry, and photometry with Convolutional Neural-Networks. - Guillaume Guiglion, Leibniz-Institut für Astrophysik Potsdam 15:00-15:04 (04min) › Unknown Unknowns: Hybrid machine learning and template based photometric redshifts - 15:04-15:08 (04min) › A Deep Learning Neural Network for Voigt Profile Fitting Quasar Absorption Lines - 15:08-15:12 (04min) › Accelerating the modeling of HI on cosmological scales via Deep Learning - 15:12-15:16 (04min) › Beyond the Hubble Sequence - Exploring galaxy morphology with unsupervised machine learning - Ting-Yun Cheng, Durham University 15:16-15:20 (04min) Contributed 15:20 - 16:05 (45min) Contributed Henri Mineur amphitheater / Plenary online session › Fast and realistic large-scale structure from machine-learning-augmented random field simulations - Davide Piras, UCL 15:20-15:35 (15min) › Parameter Estimation with Physics Informed Neural Networks - Alex Lague, University of Toronto, Canadian Institute for Theoretical Astrophysics (CITA) 15:30-16:05 (35min) › A new catalog of 343,000 quasars with their photometric redshifts derived with machine learning from the Kilo Degree Survey - Szymon Nakoneczny, National Centre for Nuclear Research [Otwock] 15:35-15:50 (15min) Break 16:05 - 16:25 (20min) Break Breakout rooms Contributed 16:25 - 17:25 (1h) Contributed Henri Mineur amphitheater / Plenary online session › Machine learning-infused cluster cosmology - Stéphane Ilic, AstroParticule et Cosmologie, Laboratoire dÉtude du Rayonnement et de la Matière en Astrophysique, Institut de recherche en astrophysique et planétologie 16:25-16:40 (15min) › CosmoPower: deep learning emulation of cosmological power spectra for accelerated Bayesian inference from next-generation surveys - Alessio Spurio Mancini, University College, London 16:40-16:55 (15min) › Single frequency CMB polarized foreground marginalization with a single training image - Niall Jeffrey, École normale supérieure 16:55-17:10 (15min) › Bayes vs. machine learning in large-scale survey demographics with eROSITA - Johannes Buchner, Max Planck Institute for Extraterrestrial Physics 17:10-17:25 (15min) Break 17:25 - 18:00 (35min) Break Breakout rooms Debate 18:00 - 19:30 (1h30) Debate Henri Mineur amphitheater / Plenary online session Cocktail dinner - Cocktail of the conference in Cassini room for in person participants 19:30 - 22:30 (3h) Cocktail dinner - Cocktail of the conference in Cassini room for in person participants Cocktail dinner	Review 10:00 - 11:00 (1h) Review Henri Mineur amphitheater / Plenary online session › Imaging Surveys and ML - Elisabeth Krause, University of Arizona 10:00-11:00 (1h) Break 11:00 - 11:20 (20min) Break Breakout rooms Contributed 11:20 - 12:20 (1h) Contributed Henri Mineur amphitheater / Plenary online session › Source detection through semantic segmentation with convolutional neural networks - Maxime Paillassa, Laboratoire dÁstrophysique de Bordeaux [Pessac], Division of Physics and Astrophysical Science, Graduate School of Science, Nagoya University 11:20-11:35 (15min) › Identifying strong gravitational lenses in current and future large-scale imaging surveys - Raoul Canameras, MPA, Garching 11:35-11:50 (15min) › Reconstructing blended galaxies with Machine Learning - Lavanya Nemani, INAF - Osservatorio Astronomico di Roma 11:50-12:05 (15min) › Pushing automated morphological classifications to their limits with the Dark Energy Survey - Jesús Vega Ferrero, Instituto de Astrofisica de Canarias 12:05-12:20 (15min) Flash talk 15:00 - 15:20 (20min) Flash talk Henri Mineur amphitheater / Plenary online session › Rediscovering Newton's gravity and Solar System properties using deep learning and inductive biases - Pablo Lemos, Department of Physics and Astronomy [UCL London], Department of physics and Astronomy [University of Sussex] 15:00-15:04 (04min) › Gaussian Process Regression: An Application to Radio Cosmology - Paula Soares, Queen Mary, University of London 15:04-15:08 (04min) › Detection of the Damped Lyman-alpha systems in quasar spectra with machine learning algorithms - ting tan, Laboratoire de Physique Nucléaire et de Hautes Énergies 15:08-15:12 (04min) › Forecasting the power of Higher Order Weak Lensing Statistics with automatically differentiable simulations - Denise lanzieri, CEA-Saclay 15:12-15:16 (04min) › Manifold learning to explore the galaxy parameter space - Iary Davidzon, DAWN/NBI - Keerthana Jegatheesan, Universidad Diego Portales - Olivier Ilbert, LAM - Clotilde Laigle, IAP 15:16-15:20 (04min) Contributed 15:20 - 16:05 (45min) Contributed Henri Mineur amphitheater / Plenary online session › Machine learning within the THREEHUNDERD simulation project - Daniel de Andres, Universidad Autonoma de Madrid 15:20-15:35 (15min) › Superresolving Herschel imaging: a proof of concept using Deep Neural Networks - Lynge Lauritsen, The Open University 15:35-15:50 (15min) › Capturing the physics of MaNGA galaxies with self-supervised Machine Learning - Regina Sarmiento, Universidad de La Laguna [Tenerife - SP], Instituto de Astrofisica de Canarias 15:50-16:05 (15min) Break 16:05 - 16:25 (20min) Break Breakout rooms Contributed Break 16:25 - 17:40 (1h15) Contributed Henri Mineur amphitheater / Plenary online session › ‘Deep' vs. 'Shallow' Learning in Cosmological Surveys - Ofer Lahav, University College London 16:25-16:40 (15min) › A Method to Distinguish Quiescent and Dusty Star-forming Galaxies with t-SNE - John Weaver, Cosmic Dawn Center 16:40-16:55 (15min) › From machine learning to human understanding - Daniel Masters, Caltech / IPAC 16:55-17:10 (15min) › Use data not models -- Lensing of '69 as an example for data-driven inference - Jenny Wagner, https://thegravitygrinch.blogspot.com 17:10-17:25 (15min) › Machine learning: lessons learnt with the QUBRICS survey - Francesco Guarneri, Astronomical Observatory of Trieste, Dipartimento di Fisica [Trieste] 17:25-17:40 (15min) 17:00 - 18:00 (1h) Break Breakout rooms Debate 18:00 - 19:30 (1h30) Debate Henri Mineur amphitheater / Plenary online session	Review 15:00 - 16:00 (1h) Review Henri Mineur amphitheater / Plenary online session › Review on generative models in Machine Learning - Gilles Loupe, Universite de Liege 15:00-16:00 (1h) Break 16:00 - 16:20 (20min) Break Breakout rooms Flash talk 16:20 - 16:40 (20min) Flash talk Henri Mineur amphitheater / Plenary online session › Studying Morphology & Quenching of Galaxies in the All Sky-Era using Interpretable Bayesian Convolutional Neural Networks - Aritra Ghosh, Yale University 16:20-16:24 (04min) › Emulating the void density profile and the void-size function - Giorgia Pollina, Universitäts-Sternwarte, Ludwig-Maximilians Universität München 16:28-16:32 (04min) › Pix2Prof: fast extraction of sequential information from galaxy imagery via a deep natural language 'captioning' model - 16:32-16:36 (04min) › Bayesian Inference Acceleration: a Deep Learning Approach - Marco Bonici, Istituto di Astrofisica Spaziale e Fisica Cosmica - Milano 16:36-16:40 (04min) Contributed 16:40 - 17:40 (1h) Contributed Henri Mineur amphitheater / Plenary online session › CosmicRIM : Reconstructing Early Universe by Combining Differentiable Simulations with Recurrent Inference Machines - Chirag Modi, Flatiron Institute 16:40-16:55 (15min) › Bridging the gap between simulations and survey data - domain adaptation for deep learning in astronomy - Aleksandra Ciprijanovic, Fermi National Accelerator Laboratory 16:55-17:10 (15min) › Stratified Learning: A general-purpose method for learning under covariate shift with applications to observational cosmology - Roberto Trotta, Department of Physics [Imperial College London], Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies 17:10-17:25 (15min) › Neural spectrum encoding - Peter Melchior, Princeton University 17:25-17:40 (15min) Coffee break 17:40 - 18:00 (20min) Coffee break Breakout rooms Debate 18:00 - 19:30 (1h30) Debate Henri Mineur amphitheater / Plenary online session	Contributed 10:00 - 11:00 (1h) Contributed Henri Mineur amphitheater / Plenary online session › The Dark Quest project for cosmological emulation - Takahiro Nishimichi, Kavli Institute for the Physics and Mathematics of the Universe [Tokyo], Yukawa Institute for Theoretical Physics 10:00-10:15 (15min) › The scattering transform in cosmology, or, a CNN without Training - Sihao Cheng, Johns Hopkins University 10:15-10:30 (15min) › Considerations for optimizing photometric classification of supernovae from the Rubin Observatory - Catarina S. Alves, University College, London 10:30-10:45 (15min) › Machine Learning Calibration of Cosmic Shear Redshift Distributions - Angus Wright, Ruhr University Bochum 10:45-11:00 (15min) Interaction session 11:00 - 11:20 (20min) Interaction session Breakout rooms Contributed 11:20 - 12:05 (45min) Contributed Henri Mineur amphitheater / Plenary online session › LyAl-Net: A high-efficiency Lyman-α forest simulation with neural network - Chotipan Boonkongkird, Sorbonne Universite 11:20-11:35 (15min) › Dark Substructure Sensitivity in the Euclid Survey with Machine Learning - Conor O'Riordan, Max Planck Institute for astrophysics 11:35-11:50 (15min) › Inferring the assembly and merger histories of galaxies with the IllustrisTNG simulations and machine learning - Lukas Eisert, Max Planck Institute for Astronomy 11:50-12:05 (15min) Flash talk 12:05 - 12:25 (20min) Flash talk Henri Mineur amphitheater / Plenary online session › Applying Deep Neural Network to dark matter halo catalogues to constrain the dark energy equation-of-state parameters - Farida Farsian, INAF - Osservatorio Astronomico di Bologna, Alma Mater Studiorum University of Bologna 12:05-12:09 (04min) › Cosmological constraints from galaxy-galaxy lensing and galaxy clustering with HSC-Y1 and BOSS data: the first application of emulator-based halo model to cosmology analysis - Hironao Miyatake, Kavli Institute for the Physics and Mathematics of the Universe [Tokyo], Nagoya University 12:09-12:13 (04min) › Tidal stream detection in HSC-SSP with Deep Learning - Helena Domínguez Sánchez, Institute of Space Sciences [Barcelona] 12:13-12:17 (04min) › Using convolutional neural networks to identify strong lenses in Euclid and J-PAS - Alberto Manjon García, Instituto de Física de Cantabria 12:17-12:21 (04min) › Galaxy Cluster Mass Estimation Using Deep Learning - Matthew Ho, Carnegie Mellon University 12:21-12:25 (04min) Review 15:00 - 16:00 (1h) Review Henri Mineur amphitheater / Plenary online session › Revue sur le machine learning et les simulations numériques - Francisco Villaescusa-Navarro, Flatiron Institute, Department of Astrophysical Sciences [Princeton] 15:00-16:00 (1h) Coffee break 16:00 - 16:20 (20min) Coffee break Breakout rooms Flash talk Contributed 16:20 - 16:40 (20min) Flash talk Henri Mineur amphitheater / Plenary online session › Photometric redshift calibration with simulated annealing and self-organising maps - Benjamin Stölzner, University College, London 16:20-16:24 (04min) › Semi-Supervised Learning for Probabilistic Photometric Redshifts - Rory Coles, National Research Council of Canada, Herzberg Astronomy & Astrophysics Program, University of Victoria 16:24-16:28 (04min) › Time Delay Estimation in Unresolved Lensed Quasars via Convolutioanl Neural Networks - Luca Biggio, ETH - Alba Domi, University of Genoa - Luca Paganin, University of Genoa 16:28-16:32 (04min) › Detection of the Damped Lyman-alpha systems in quasar spectra with machine learning algorithms - ting tan, Laboratoire de Physique Nucléaire et de Hautes Énergies 16:32-16:36 (04min) 16:35 - 17:20 (45min) Contributed Henri Mineur amphitheater / Plenary online session › Real-time science-driven follow-up of survey transients: Optimally augmenting ZTF SN Ia light curves for maximizing SALT2 parameter constraints - 16:35-16:50 (15min) › What drives the scatter in the BPT diagrams? A Machine Learning based analysis - 16:50-17:05 (15min) › Quantifying uncertainty in deep-learning classification of radio galaxies - 17:05-17:20 (15min) Coffee break 17:20 - 18:00 (40min) Coffee break Breakout rooms Debate 18:00 - 19:30 (1h30) Debate Henri Mineur amphitheater / Plenary online session Conference Dinner 20:30 - 23:00 (2h30) Conference Dinner Conference dinner pour in person participation	Review 10:00 - 11:00 (1h) Review Henri Mineur amphitheater / Plenary online session › Review on Exoplanets and Machine Learning - Ingo Waldmann, University College London - London's Global University 10:00-11:00 (1h) Interaction session 11:00 - 11:20 (20min) Interaction session Breakout rooms Contributed 11:20 - 12:20 (1h) Contributed Henri Mineur amphitheater / Plenary online session › An hybrid physics-ML framework to model exoplanetary light curves - Mario Morvan, University College London - London's Global University 11:20-11:35 (15min) › A deep transfer learning approach to photospheric parameters of CARMENES target stars - Antonio Bello-Garcia, University of Oviedo 11:35-11:50 (15min) › Multifrequency Point Source detection with Fully-Convolutional Networks: Performance in realistic microwave sky simulations - José Manuel Casas, Instituto Universitario de Ciencias y Tecnologías Espaciales de Asturias (ICTEA), University of Oviedo, Department of Physics 11:50-12:05 (15min) › Using a series Machine Learning models for the detection of high-redshift Radio Galaxy candidates. - Rodrigo Carvajal, Institute of Astrophysics and Space Sciences - University of Lisbon 12:05-12:20 (15min) Review 15:00 - 16:00 (1h) Review Henri Mineur amphitheater / Plenary online session › Review on Machine Learning for Radio-astronomy - Michelle Lochner, University of the Western Cape, South African Radio Astronomy Observatory, African Institute for Mathematical Sciences 15:00-16:00 (1h) Coffee break 16:00 - 16:20 (20min) Coffee break Breakout rooms Contributed Interaction session 16:20 - 17:20 (1h) Contributed Henri Mineur amphitheater / Plenary online session › hyphy: Mapping Dark Matter to Hydrodynamics with Posterior Inference - Benjamin A Horowitz, Department of Astrophysical Sciences [Princeton] 16:20-16:35 (15min) › MINERVA team: Winning the SKA Science Data Challenge 2 with fast dedicated CNN architectures - David Cornu, Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique 16:35-16:50 (15min) › Inference and probabilistic modelling with machine learning for LISA data analysis - Natalia Korsakova, Systèmes de Référence Temps Espace 16:50-17:05 (15min) › Deep Neural Networks for detection of sources in radio astronomical maps: main challenges and current achievements. - Renato Sortino, INAF - Osservatorio Astrofisico di Catania - Daniel Magro, University of Malta [Malta] 17:05-17:20 (15min) 17:00 - 18:00 (1h) Interaction session Breakout rooms Conference summary 18:00 - 18:10 (10min) Conference summary Henri Mineur amphitheater / Plenary online session Brice Ménard (JHU) Debate 18:10 - 19:40 (1h30) Debate Henri Mineur amphitheater / Plenary online session Concluding remarks 19:40 - 19:50 (10min) Concluding remarks Henri Mineur amphitheater / Plenary online session

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