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Haber, Eldad

  1. Deep Neural Networks Motivated by Partial Differential Equations
    2018/04/12 by Ruthotto, Lars, Haber, Eldad · 22 citations
    #65K10 #68T45 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  2. AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
    2019/02/26 by Bo Chang, Minmin Chen, Chang, Bo +5 · 6 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Model Reduction and Neural Networks #Neural Networks and Applications
  3. PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations
    2021/08/04 by Moshe Eliasof, Eldad Haber, Eliasof, Moshe +3 · 8 citations
    Physics and Astronomy · Computer Science · Materials Science · #Model Reduction and Neural Networks #Advanced Graph Neural Networks #Machine Learning in Materials Science
  4. An Introduction to Deep Generative Modeling
    2021/03/09 by Ruthotto, Lars, Haber, Eldad · 7 citations
    #68T07 #FOS: Computer and information sciences #Machine Learning (cs.LG)
  5. Neural-networks for geophysicists and their application to seismic data\n interpretation
    2019/03/26 by Bas Peters, Peters, Bas, Eldad Haber +3 · 1 voice
    Earth and Planetary Sciences · Engineering · #Seismic Imaging and Inversion Techniques #Reservoir Engineering and Simulation Methods #Hydraulic Fracturing and Reservoir Analysis
  6. Reversible Architectures for Arbitrarily Deep Residual Neural Networks
    2017/09/12 by Bo Chang, Chang, Bo, Lili Meng +9 · 4 citations
    Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  7. Multi-level Residual Networks from Dynamical Systems View
    2017/10/27 by Chang, Bo, Meng, Lili, Haber, Eldad +2 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (stat.ML)
  8. jInv -- a flexible Julia package for PDE parameter estimation
    2016/06/23 by Ruthotto, Lars, Treister, Eran, Haber, Eldad · 2 citations
    #FOS: Computer and information sciences #Mathematical Software (cs.MS)
  9. Feature Transportation Improves Graph Neural Networks
    2023/07/29 by Moshe Eliasof, Eldad Haber, Eliasof, Moshe +3 · 4 citations
    Computer Science · #Advanced Graph Neural Networks #Recommender Systems and Techniques #Machine Learning and ELM
  10. Multi-resolution neural networks for tracking seismic horizons from few\n training images
    2018/12/26 by Bas Peters, Peters, Bas, Justin Granek +3 · 1 citation
    Earth and Planetary Sciences · Engineering · #Seismic Imaging and Inversion Techniques #Reservoir Engineering and Simulation Methods #Hydraulic Fracturing and Reservoir Analysis
  11. Fully Hyperbolic Convolutional Neural Networks
    2019/05/24 by Keegan Lensink, Lensink, Keegan, Bas Peters +3 · 1 citation
    Computer Science · Physics and Astronomy · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
  12. IMEXnet: A Forward Stable Deep Neural Network
    2019/03/06 by Haber, Eldad, Lensink, Keegan, Treister, Eran +1 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  13. Paired Autoencoders for Likelihood-free Estimation in Inverse Problems
    2024/05/21 by Matthias Chung, Chung, Matthias, Emma Hart +7 · 2 citations
    Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Neural Networks and Applications #Numerical Analysis (math.NA) #Radiative Heat Transfer Studies
  14. DRIP: Deep Regularizers for Inverse Problems
    2023/03/30 by Eliasof, Moshe, Haber, Eldad, Treister, Eran · 1 citation
    #Computational Engineering #FOS: Computer and information sciences #Finance #Machine Learning (cs.LG) #and Science (cs.CE)
  15. Graph Neural Reaction Diffusion Models
    2024/06/16 by Moshe Eliasof, Eliasof, Moshe, Eldad Haber +3 · 1 citation
    Computer Science · Biochemistry, Genetics and Molecular Biology · #Neural Networks and Applications #Computational Drug Discovery Methods #Gene Regulatory Network Analysis
  16. Towards Efficient Training of Graph Neural Networks: A Multiscale Approach
    2025/03/25 by Gal, Eshed, Eliasof, Moshe, Schönlieb, Carola-Bibiane +3 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  17. Learning Regularization for Graph Inverse Problems
    2024/08/19 by Moshe Eliasof, Eliasof, Moshe, Md Shahriar Rahim Siddiqui +5 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning and ELM