Publications

Journal papers

• Quantifying the informativity of emission lines to infer physical conditions in giant molecular clouds.
  I. Application to model predictions  
  L. Einig, P. Palud, A. Roueff, J. Pety, et al.
  Astronomy & Astrophysics, 2024
  

• Neural network-based emulation of interstellar medium models  
  P. Palud, L. Einig, F. Le Petit, E. Bron, et al.
  Astronomy & Astrophysics, 2023
  

• Deep learning denoising by dimension reduction: Application to the ORION-B line cubes  
  L. Einig, J. Pety, A. Roueff, P. Vandame, et al.
  Astronomy & Astrophysics, 2023

National conferences

• Réduction d’un modèle astrophysique par réseaux de neurones    
  L. Einig, P. Palud, J. Chanussot, J. Pety, et al.
  GRETSI'23, 2023
  

Workshop and conference abstracts

• An information-theory based method to determine the best emission lines to constrain the physical conditions of interstellar clouds    
  PCMI, 2024
  

• Deep learning denoising of molecular line cubes by dimension reduction  
  DeepLearning3D, 2024
  

• Neural network-based emulation of interstellar medium models  
  SF2A, 2024
  

• Efficient and fast deep learning approaches to denoise large radioastronomy line cubes ​and to emulate sophisticated astrophysical models  
  ML-IAP/CCA, 2023
  

• Deep learning denoising by dimension reduction: Application to molecular line cubes    
  Olympian Symposium, 2023