Graph Normalizing Flows

30 May 2019

Jimmy Ba

Papers citing "Graph Normalizing Flows"

25 / 25 papers shown

Title
HOG-Diff: Higher-Order Guided Diffusion for Graph Generation Yiming Huang Tolga Birdal DiffM 76 0 0 06 Feb 2025
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities Daniel Zilberg Ron Levie 31 0 0 18 Sep 2024
Probabilistic Forecasting of Irregular Time Series via Conditional Flows Vijaya Krishna Yalavarthi Randolf Scholz Stefan Born Lars Schmidt-Thieme AI4TS 30 0 0 09 Feb 2024
GC-Flow: A Graph-Based Flow Network for Effective Clustering Tianchun Wang F. Mirzazadeh X. Zhang Jing Chen BDL 37 6 0 26 May 2023
Sample Complexity of Probability Divergences under Group Symmetry Ziyu Chen M. Katsoulakis Luc Rey-Bellet Weixia Zhu 18 10 0 03 Feb 2023
E(n)-equivariant Graph Neural Cellular Automata G. Gala Daniele Grattarola Erik Quaeghebeur GNN 34 3 0 25 Jan 2023
Normalizing Flows for Human Pose Anomaly Detection Or Hirschorn S. Avidan 3DH 14 46 0 20 Nov 2022
NVDiff: Graph Generation through the Diffusion of Node Vectors Xiaohui Chen Yukun Li Aonan Zhang Liping Liu DiffM 15 21 0 19 Nov 2022
Fast Graph Generation via Spectral Diffusion Tianze Luo Zhanfeng Mo Sinno Jialin Pan DiffM 13 22 0 16 Nov 2022
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions Paweł Antoni Pierzchlewicz R. J. Cotton Mohammad Ali Bashiri Fabian H. Sinz 3DH 21 8 0 20 Oct 2022
Diffusion Models for Graphs Benefit From Discrete State Spaces K. Haefeli Karolis Martinkus Nathanael Perraudin Roger Wattenhofer DiffM 83 51 0 04 Oct 2022
Text to Image Synthesis using Stacked Conditional Variational Autoencoders and Conditional Generative Adversarial Networks Haileleol Tibebu Aadin Malik V. D. Silva GAN 18 7 0 06 Jul 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 41 104 0 16 May 2022
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators Karolis Martinkus Andreas Loukas Nathanael Perraudin Roger Wattenhofer 27 66 0 04 Apr 2022
Semi-Discrete Normalizing Flows through Differentiable Tessellation Ricky T. Q. Chen Brandon Amos Maximilian Nickel 22 10 0 14 Mar 2022
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations Jaehyeong Jo Seul Lee Sung Ju Hwang DiffM 19 207 0 05 Feb 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation Emma R. Cobian J. Hauenstein Fang Liu Daniele E. Schiavazzi 6 4 0 01 Feb 2022
Training Graph Neural Networks with 1000 Layers Guohao Li Matthias Muller Bernard Ghanem V. Koltun GNN AI4CE 34 235 0 14 Jun 2021
E(n) Equivariant Graph Neural Networks Victor Garcia Satorras Emiel Hoogeboom Max Welling 28 974 0 19 Feb 2021
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 31 145 0 13 Jul 2020
Categorical Normalizing Flows via Continuous Transformations Phillip Lippe E. Gavves BDL 13 43 0 17 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 17 7 0 05 Jun 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 41 425 0 26 Jan 2020
Graph Neural Ordinary Differential Equations Michael Poli Stefano Massaroli Junyoung Park Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 25 154 0 18 Nov 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 26 5,390 0 20 Dec 2018