AstroAI Workshop 2024
Contributed Talks:
- Anshuman Acharya: A Machine Learning Upgrade to GPR for EoR 21-cm signal extraction from LOFAR data
- Gregoire Aufort: Inferring Star formation histories with neural density estimation and cosmological simulations
- Vishnu Balakrishnan: PulsarNet - Accelerating the Discovery of Binary Pulsars through Attention-Based Neural Networks
- Joshua Fagin: Latent Stochastic Differential Equations for Modeling Quasar Variability
- Trung Ha: Segmentation of Current Sheets in Magnetized Plasma Turbulence with Computer Vision
- Ashod Khederlarian: Deep Learning Photo-z's in Preparation for Roman
- Nolan Koblischke: SpectraFM: Tuning into Stellar Foundation Models
- David Krejcik: Improving Fast Radio Burst Localizations Using Simulation-Based Inference
- Thibault Lechien: Accelerating neutron star light curve simulation and parameter inference through neural networks
- Zachary Murray: Using neural networks to model Main Belt Asteroid albedos as a function of their proper orbital elements
- Daniel Muthukrishna: Modeling Image Systematics Using Conditional Diffusion Models
- Tri Nguyen: How DREAMS are made: Emulating subhalo populations under alternative dark matter scenarios with Variational Diffusion Models
- Core Francisco Park: Probabilistic Reconstruction of the Local Dark Matter with 3D Diffusion Models
- Lucas Pulgar-Escobar: COSMIC: Characterization of Star clusters using Machine-learning Inference and Clustering
- Gabriel Sasseville: Interpolation of Sagittarius A* multiwavelength data using a transformer based machine learning model
- Alexander Stone-Martinez: Improving Stellar Age Estimations with Normalizing Flows
- Ethan Tregidga: Probing Self-Interacting Dark Matter with Interpretable Neural Networks
- Stephane Werner: Applying Machine Learning to Determine Galaxy Membership in Galaxy Clusters
Posters:
- Malapaka Venkata Ratna Abhishek: Detection of possible depletion duration of boundary layer structure in a Z source GX 349+2.
- Naresh Adhikari: Multimessenger search pipeline with gravitational wave, electromagnetic wave or neutrinos
- S M Rafee Adnan: Exploring the Mass-Metallicity Relation in Open Clusters inside the Milky Way
- Juan Pablo Alfonzo: Katachi (形): Decoding the Imprints of Past Star Formation on Present-Day Morphology in Galaxies with Interpretable CNNs
- Toka Alokda: Identification of Protohalos with Deep Learning
- Amina Diop: Uncovering the Molecular Recipe for Protoplanetary Disk Masses
- Ahmad Ibrahim: Revealing the mystery of the M87 jets
- Jenna Karcheski: Obtaining Magnetic Fields in Molecular Clouds using Denoising Diffusion Probabilistic Models
- Bikash Kharel: A Machine Learning Approach to Morphological Distinction of Repeating vs Non-Repeating Fast Radio Bursts.
- Sayed Shafaat Mahmud: Using Neural Networks to detect Dark Star Candidates in the Early Universe
- Nicolás Andrés Henríquez Salgado: Characterizing X-GAP galaxy groups dynamical state and substructures with machine learning implementations
- Mike Smith: Neural scaling laws and astronomy
- John Soltis: Estimating Galaxy Cluster Mass Accretion Rates from Observations using Machine Learning
- Kyle Tregoning: Theia 456: Tidally Shredding an Open Cluster
- Christopher Weinert: An Artificial Neural Network for on-board event pre-processing of Gamma-Ray Burst Observations