Scalable Normalizing Flows for Permutation Invariant Densities

Scalable Normalizing Flows for Permutation Invariant Densities

7 October 2020

Stephan Günnemann

Papers citing "Scalable Normalizing Flows for Permutation Invariant Densities"

8 / 8 papers shown

Title
Learning with Exact Invariances in Polynomial Time Ashkan Soleymani B. Tahmasebi Stefanie Jegelka Patrick Jaillet 78 0 0 27 Feb 2025
Probabilistic Forecasting of Irregular Time Series via Conditional Flows Vijaya Krishna Yalavarthi Randolf Scholz Stefan Born Lars Schmidt-Thieme AI4TS 35 0 0 09 Feb 2024
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics Koen Minartz Y. Poels Simon Koop Vlado Menkovski 30 5 0 23 May 2023
Statistical Guarantees of Group-Invariant GANs Ziyu Chen M. Katsoulakis Luc Rey-Bellet Wei-wei Zhu 47 2 0 22 May 2023
Sample Complexity of Probability Divergences under Group Symmetry Ziyu Chen M. Katsoulakis Luc Rey-Bellet Weixia Zhu 32 10 0 03 Feb 2023
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 35 9 0 13 Sep 2022
Semi-Discrete Normalizing Flows through Differentiable Tessellation Ricky T. Q. Chen Brandon Amos Maximilian Nickel 32 10 0 14 Mar 2022
Neural Flows: Efficient Alternative to Neural ODEs Marin Bilovs Johanna Sommer Syama Sundar Rangapuram Tim Januschowski Stephan Günnemann AI4TS 21 70 0 25 Oct 2021