Machine Learning and Many Particle Physics

Papers

  • 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.
    2015.
    pdfarXiv.