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publications:annualreports:saig_21 [2021/01/24 22:49]
msacchi
publications:annualreports:saig_21 [2022/01/24 04:41] (current)
msacchi
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-====== SAIG-20 (2020) ======+====== SAIG-21 (2020) ======
  
 ---- ----
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 <fc #​008000>​SAIG 21-4 (2020) Fernanda Carozzi </​fc>​\\ <fc #​008000>​SAIG 21-4 (2020) Fernanda Carozzi </​fc>​\\
-<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_04.pdf |Robust reconstruction via a generalized loss function }}</​WRAP>​+<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_04.pdf |Robust reconstruction via a generalized loss function }}\\ 
 +Julia package {{sponsorsandstudents:​Robust_Reconstruction_GLF.zip| Robust_Reconstrtuction_GLF.zip}} 
 +</​WRAP>​
  
 <fc #​008000>​SAIG 21-5 (2020) Ji Li and M D sacchi </​fc>​\\ <fc #​008000>​SAIG 21-5 (2020) Ji Li and M D sacchi </​fc>​\\
-<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_05.pdf |Deblending via Fast Robust Greedy Pursuit }}</​WRAP>​+<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_05.pdf |Deblending via Fast Robust Greedy Pursuit }}\\ 
 +Matlab package {{sponsorsandstudents:​Robust_MP.zip| Robust_MP.zip}} 
 +</​WRAP>​
  
 <fc #​008000>​SAIG 21-6 (2020) Breno Bahia, Rongzhi Lin and M D Sacchi</​fc>​\\ <fc #​008000>​SAIG 21-6 (2020) Breno Bahia, Rongzhi Lin and M D Sacchi</​fc>​\\
-<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_06.pdf |Regularization by Denoising for simultaneous source separation }}</​WRAP>​+<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_06.pdf |Regularization by Denoising for simultaneous source separation }} 
 +\\ 
 +Julia package {{sponsorsandstudents:​RED_Deblending.zip| RED_Deblending.zip}} 
 +</​WRAP>​
  
 <fc #​008000>​SAIG 21-7 (2020) Breno Bahia and M D Sacchi</​fc>​\\ <fc #​008000>​SAIG 21-7 (2020) Breno Bahia and M D Sacchi</​fc>​\\
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 <fc #​008000>​SAIG 21-8 (2020) Breno Bahia and M D Sacchi</​fc>​\\ <fc #​008000>​SAIG 21-8 (2020) Breno Bahia and M D Sacchi</​fc>​\\
-<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_08.pdf |From low rank matrices to sparse vectors in the presence of atypical observations+<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_08.pdf |From low-rank matrices to sparse vectors in the presence of atypical observations
  ​}}</​WRAP>​  ​}}</​WRAP>​
  
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 <fc #​008000>​SAIG 21-9 (2020) Kristian D. T. Bautista and Mauricio Sacchi</​fc>​\\ <fc #​008000>​SAIG 21-9 (2020) Kristian D. T. Bautista and Mauricio Sacchi</​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_09.pdf |Deep-LSRTM:​ Solving least-squares reverse time migration with learned updating operators <WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_09.pdf |Deep-LSRTM:​ Solving least-squares reverse time migration with learned updating operators
-}}</​WRAP>​+}}\\ 
 +Python/​TensorFlow package: Contact Kristian for Dockerfile 
 +</​WRAP>​
  
  
  
 <fc #​008000>​SAIG 21-10 (2020) Amsalu Anagaw and Mauricio Sacchi</​fc>​\\ <fc #​008000>​SAIG 21-10 (2020) Amsalu Anagaw and Mauricio Sacchi</​fc>​\\
-<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_10.pdf |Regularization by Denoising (RED) with adaptive-weighted Total Variation for 3D FWI model updates in large- contrast media+<WRAP indent>​{{:​sponsorsandstudents:​saig21r:​chap_10.pdf |Regularization by Denoising (RED) with adaptive-weighted Total Variation for 3D FWI model updates in large-contrast media
 }}</​WRAP>​ }}</​WRAP>​
  
publications/annualreports/saig_21.1611528561.txt.gz · Last modified: 2021/01/24 22:49 by msacchi