1 code implementation • ICLR 2022 • Antoine Brochard, Sixin Zhang, Stéphane Mallat
State-of-the-art maximum entropy models for texture synthesis are built from statistics relying on image representations defined by convolutional neural networks (CNN).
2 code implementations • 27 Oct 2020 • Antoine Brochard, Bartłomiej Błaszczyszyn, Stéphane Mallat, Sixin Zhang
This paper presents a statistical model for stationary ergodic point processes, estimated from a single realization observed in a square window.
no code implementations • 9 Jun 2020 • Bartek Błaszczyszyn, Antoine Brochard, H. Paul Keeler
We propose a new class of algorithms for randomly scheduling network transmissions.
3 code implementations • 11 Sep 2019 • Francisco Villaescusa-Navarro, ChangHoon Hahn, Elena Massara, Arka Banerjee, Ana Maria Delgado, Doogesh Kodi Ramanah, Tom Charnock, Elena Giusarma, Yin Li, Erwan Allys, Antoine Brochard, Chi-Ting Chiang, Siyu He, Alice Pisani, Andrej Obuljen, Yu Feng, Emanuele Castorina, Gabriella Contardo, Christina D. Kreisch, Andrina Nicola, Roman Scoccimarro, Licia Verde, Matteo Viel, Shirley Ho, Stephane Mallat, Benjamin Wandelt, David N. Spergel
The Quijote simulations are a set of 44, 100 full N-body simulations spanning more than 7, 000 cosmological models in the $\{\Omega_{\rm m}, \Omega_{\rm b}, h, n_s, \sigma_8, M_\nu, w \}$ hyperplane.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
no code implementations • 19 Dec 2018 • Antoine Brochard, Bartłomiej Błaszczyszyn, Stéphane Mallat, Sixin Zhang
To approximate (interpolate) the marking function, in our baseline approach, we build a statistical regression model of the marks with respect some local point distance representation.