ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1809.02630
  4. Cited By
Constrained Generation of Semantically Valid Graphs via Regularizing
  Variational Autoencoders

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

7 September 2018
Tengfei Ma
Jie Chen
Cao Xiao
ArXivPDFHTML

Papers citing "Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders"

27 / 27 papers shown
Title
An Information-Theoretic Regularizer for Lossy Neural Image Compression
An Information-Theoretic Regularizer for Lossy Neural Image Compression
Y. Zhang
Meng Wang
Xihua Sheng
Peilin Chen
Junru Li
L. Zhang
S. Wang
151
0
0
23 Nov 2024
GP-MoLFormer: A Foundation Model For Molecular Generation
GP-MoLFormer: A Foundation Model For Molecular Generation
Jerret Ross
Brian M. Belgodere
Samuel C. Hoffman
Vijil Chenthamarakshan
Youssef Mroueh
Payel Das
Payel Das
31
5
0
04 Apr 2024
Overcoming Order in Autoregressive Graph Generation
Overcoming Order in Autoregressive Graph Generation
Edo Cohen-Karlik
Eyal Rozenberg
Daniel Freedman
30
1
0
04 Feb 2024
Interpreting Equivariant Representations
Interpreting Equivariant Representations
Andreas Abildtrup Hansen
Anna Calissano
Aasa Feragen
45
1
0
23 Jan 2024
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural
  Network
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network
Akihiro Kishimoto
Hiroshi Kajino
Masataka Hirose
Junta Fuchiwaki
Indra Priyadarsini
Lisa Hamada
Hajime Shinohara
D. Nakano
Seiji Takeda
AI4CE
16
4
0
28 Sep 2023
The Expressive Power of Graph Neural Networks: A Survey
The Expressive Power of Graph Neural Networks: A Survey
Bingxue Zhang
Changjun Fan
Shixuan Liu
Kuihua Huang
Xiang Zhao
Jin-Yu Huang
Zhong Liu
40
19
0
16 Aug 2023
Fast Graph Generation via Spectral Diffusion
Fast Graph Generation via Spectral Diffusion
Tianze Luo
Zhanfeng Mo
Sinno Jialin Pan
DiffM
13
22
0
16 Nov 2022
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders
Kiarash Zahirnia
Oliver Schulte
Parmis Naddaf
Ke Li
27
10
0
30 Oct 2022
Controllable Data Generation by Deep Learning: A Review
Controllable Data Generation by Deep Learning: A Review
Shiyu Wang
Yuanqi Du
Xiaojie Guo
Bo Pan
Zhaohui Qin
Liang Zhao
29
28
0
19 Jul 2022
LIMO: Latent Inceptionism for Targeted Molecule Generation
LIMO: Latent Inceptionism for Targeted Molecule Generation
Peter Eckmann
Kunyang Sun
Bo-Lu Zhao
Mudong Feng
Michael K. Gilson
Rose Yu
BDL
32
44
0
17 Jun 2022
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular
  Linker Design
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design
Yinan Huang
Xing Peng
Jianzhu Ma
Muhan Zhang
BDL
28
47
0
15 May 2022
SELFIES and the future of molecular string representations
SELFIES and the future of molecular string representations
Mario Krenn
Qianxiang Ai
Senja Barthel
Nessa Carson
Angelo Frei
...
Andrew Wang
Andrew D. White
A. Young
Rose Yu
A. Aspuru‐Guzik
22
147
0
31 Mar 2022
Deep Graph Learning for Anomalous Citation Detection
Deep Graph Learning for Anomalous Citation Detection
Jiaying Liu
Feng Xia
Xu Feng
Jing Ren
Huan Liu
22
40
0
23 Feb 2022
Score-based Generative Modeling of Graphs via the System of Stochastic
  Differential Equations
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
Jaehyeong Jo
Seul Lee
Sung Ju Hwang
DiffM
22
210
0
05 Feb 2022
GraphDF: A Discrete Flow Model for Molecular Graph Generation
GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo
Keqiang Yan
Shuiwang Ji
DRL
171
187
0
01 Feb 2021
A Systematic Survey on Deep Generative Models for Graph Generation
A Systematic Survey on Deep Generative Models for Graph Generation
Xiaojie Guo
Liang Zhao
MedIm
35
145
0
13 Jul 2020
Categorical Normalizing Flows via Continuous Transformations
Categorical Normalizing Flows via Continuous Transformations
Phillip Lippe
E. Gavves
BDL
13
43
0
17 Jun 2020
Graph Deconvolutional Generation
Graph Deconvolutional Generation
Daniel Flam-Shepherd
Tony C Wu
Alán Aspuru-Guzik
BDL
17
31
0
14 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph
  Generation
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
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy
Tianfan Fu
Cao Xiao
Jimeng Sun
20
63
0
23 Nov 2019
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular
  string representation
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation
Mario Krenn
Florian Hase
AkshatKumar Nigam
Pascal Friederich
Alán Aspuru-Guzik
6
70
0
31 May 2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
Muhan Zhang
Shali Jiang
Zhicheng Cui
Roman Garnett
Yixin Chen
GNN
BDL
CML
21
196
0
24 Apr 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating
  Knowledge into Learning Systems
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden
S. Mayer
Katharina Beckh
B. Georgiev
Sven Giesselbach
...
Rajkumar Ramamurthy
Michal Walczak
Jochen Garcke
Christian Bauckhage
Jannis Schuecker
34
626
0
29 Mar 2019
Learning to Sample Hard Instances for Graph Algorithms
Learning to Sample Hard Instances for Graph Algorithms
Ryoma Sato
M. Yamada
H. Kashima
11
1
0
26 Feb 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaML
GNN
AI4TS
AI4CE
150
8,342
0
03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications
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
28
5,397
0
20 Dec 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
219
1,337
0
12 Feb 2018
1