Scattering Transforms and Deep Learning


3D Scattering Transforms and Particle Physics

  • Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties.
    With Paul Sinz, Michael Swift, Xavier Brumwell, Jialin Liu, Kwang Jin Kim and Yue Qi.
    The Journal of Chemical Physics, volume 153, issue 8, 084109, 2020.
    pdf, arXiv, AIP.
  • Steerable Wavelet Scattering for 3D Atomic Systems with Application to Li-Si Energy Prediction (contributed spotlight talk).
    With Xavier Brumwell, Paul Sinz, Kwang Jin Kim and Yue Qi.
    In NeurIPS Workshop on Machine Learning for Molecules and Materials, Montreal, Canada, December 8, 2018.
    pdf, arXiv, NIPS MLMM.
  • Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties (Editor’s Pick).
    With Michael Eickenberg, Georgios Exarchakis, Stéphane Mallat and Louis Thiry.
    Journal of Chemical Physics, volume 148, issue 24, 241732, 2018.
    pdf, arXiv, AIP. Software.
  • Solid Harmonic Wavelet Scattering.
    With Michael Eickenberg, Georgios Exarchakis and Stéphane Mallat.
    Advances in Neural Information Processing Systems 30 (NIPS 2017), pages 6543-6552, 2017.
    pdf, NIPS Proceedings.
  • Wavelet Scattering Regression of Quantum Chemical Energies.
    With Stéphane Mallat and Nicolas Poilvert.
    Multiscale Modeling and Simulation, volume 15, issue 2, 827-863, 2017.
    pdfarXiv, MMSSoftware.
  • Quantum Energy Regression using Scattering Transforms.
    With Nicolas Poilvert and Stéphane Mallat.

Geometric Deep Learning on Manifolds and Graphs

  • MagNet: A Magnetic Neural Network for Directed Graphs.
    With Xitong Zhang, Yixuan He, Nathan Brugnone, and Michael Perlmutter.
    In Advances in Neural Information Processing Systems 34, 2021.
    pdf, arXiv, NeurIPS. Software.
  • ClassicalGSG: Prediction of logP Using Classical Molecular Force Fields and Geometric Scattering for Graphs.
    With Nazanin Donyapour and Alex Dickson.
    Journal of Computational Chemistry, volume 42, issues 14, pages 1006-1017, 2021.
    pdf, ChemRxiv, Journal of Comp. Chem. Software.
  • Geometric scattering networks on compact Riemannian manifolds.
    With Michael Perlmutter, Feng Gao and Guy Wolf.
    Proceedings of The First Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research, volume 107, pages 570–604, 2020.
    pdf, arXiv, PMLR.
  • Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms.
    With Michael Perlmutter, Feng Gao and Guy Wolf.
    pdf, arXiv.
  • Geometric wavelet scattering on graphs and manifolds.
    With Feng Gao, Michael Perlmutter and Guy Wolf.
    In Proceedings of SPIE 11138, Wavelets and Sparsity XVIII, 111380Q, 2019.
    pdf, SPIE.
  • Geometric Scattering for Graph Data Analysis.
    With Feng Gao and Guy Wolf.
    In Proceedings of the 36th International Conference on Machine Learning, Proceedings of Machine Learning Research (PMLR), volume 97, pages 2122-2131, 2019.
    pdf, ICML/PMLR, arXiv.
  • Geometric Scattering on Manifolds (contributed spotlight talk).
    With Michael Perlmutter and Guy Wolf.
    In NeurIPS Workshop on Integration of Deep Learning Theories, Montreal, Canada, December 8, 2018.
    pdf, arXiv, NIPS DLTheory.

Inverse Problems related to Cryo-EM

  • Unbiasing Procedures for Scale-invariant Multi-reference Alignment.
    With Anna Little.
    pdf, arXiv. Software.
  • Wavelet invariants for statistically robust multi-reference alignment.
    With Anna Little.
    Information and Inference: A Journal of the IMA, in press, 2020.
    pdf, arXiv, IMA. Software.

Statistical Scattering Moments for Stochastic Processes

  • Texture synthesis via projection onto multiscale, multilayer statistics.
    With Jieqian He.
    pdf, arXiv.
  • Scattering Statistics of Generalized Spatial Poisson Point Processes.
    With Michael Perlmutter and Jieqian He.
    pdf, arXiv.

Software Papers

  • Kymatio: Scattering Transforms in Python.
    With Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gasper Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Edouard Oyallon, Sixhin Zhang, Carmine Cella, Michael Eickenberg.
    Journal of Machine Learning Research, volume 21, number 60, pages 1-6, 2020.
    pdf, arXiv, JMLR. Software.