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Overcoming Order in Autoregressive Graph Generation

Overcoming Order in Autoregressive Graph Generation

4 February 2024
Edo Cohen-Karlik
Eyal Rozenberg
Daniel Freedman
ArXiv (abs)PDFHTML

Papers citing "Overcoming Order in Autoregressive Graph Generation"

44 / 44 papers shown
Title
Size Matters: Large Graph Generation with HiGGs
Size Matters: Large Graph Generation with HiGGs
Alex O. Davies
Nirav Ajmeri
Telmo de Menezes e Silva Filho
71
3
0
20 Jun 2023
Let There Be Order: Rethinking Ordering in Autoregressive Graph
  Generation
Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation
Jie Bu
Kazi Sajeed Mehrab
Anuj Karpatne
74
3
0
24 May 2023
Equivariant Diffusion for Molecule Generation in 3D
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom
Victor Garcia Satorras
Clément Vignac
Max Welling
DiffM
123
608
0
31 Mar 2022
A Survey on Deep Graph Generation: Methods and Applications
A Survey on Deep Graph Generation: Methods and Applications
Yanqiao Zhu
Yuanqi Du
Yinkai Wang
Yichen Xu
Jieyu Zhang
Qiang Liu
Shu Wu
3DVGNN
105
73
0
13 Mar 2022
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
280
30,103
0
01 Mar 2022
Disentangled Spatiotemporal Graph Generative Models
Disentangled Spatiotemporal Graph Generative Models
Yuanqi Du
Xiaojie Guo
Hengning Cao
Yanfang Ye
Liang Zhao
87
21
0
28 Feb 2022
Interpretable Molecular Graph Generation via Monotonic Constraints
Interpretable Molecular Graph Generation via Monotonic Constraints
Yuanqi Du
Xiaojie Guo
Amarda Shehu
Liang Zhao
93
19
0
28 Feb 2022
Keeping it Simple: Language Models can learn Complex Molecular
  Distributions
Keeping it Simple: Language Models can learn Complex Molecular Distributions
Daniel Flam-Shepherd
Kevin Zhu
A. Aspuru‐Guzik
207
148
0
06 Dec 2021
Inverse design of 3d molecular structures with conditional generative
  neural networks
Inverse design of 3d molecular structures with conditional generative neural networks
Niklas W. A. Gebauer
M. Gastegger
Stefaan S. P. Hessmann
Klaus-Robert Muller
Kristof T. Schütt
AI4CE
225
173
0
10 Sep 2021
Evaluating Large Language Models Trained on Code
Evaluating Large Language Models Trained on Code
Mark Chen
Jerry Tworek
Heewoo Jun
Qiming Yuan
Henrique Pondé
...
Bob McGrew
Dario Amodei
Sam McCandlish
Ilya Sutskever
Wojciech Zaremba
ELMALM
231
5,539
0
07 Jul 2021
Order Matters: Probabilistic Modeling of Node Sequence for Graph
  Generation
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen
Xu Han
Jiajing Hu
Francisco J. R. Ruiz
Liping Liu
BDL
43
35
0
11 Jun 2021
Regularizing Towards Permutation Invariance in Recurrent Models
Regularizing Towards Permutation Invariance in Recurrent Models
Edo Cohen-Karlik
Avichai Ben David
Amir Globerson
OOD
89
16
0
25 Oct 2020
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
93
150
0
13 Jul 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Chengxi Zang
Fei Wang
BDL
122
293
0
17 Jun 2020
A Deep Generative Model for Fragment-Based Molecule Generation
A Deep Generative Model for Fragment-Based Molecule Generation
Marco Podda
D. Bacciu
Alessio Micheli
VLMBDL
60
52
0
28 Feb 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
G. Simm
Robert Pinsler
José Miguel Hernández-Lobato
AI4CE
64
85
0
18 Feb 2020
Graph Deconvolutional Generation
Graph Deconvolutional Generation
Daniel Flam-Shepherd
Tony C Wu
Alán Aspuru-Guzik
BDL
136
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
168
438
0
26 Jan 2020
GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph
  Generation
GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation
Nikhil Goyal
Harsh Jain
Sayan Ranu
45
92
0
22 Jan 2020
Efficient Graph Generation with Graph Recurrent Attention Networks
Efficient Graph Generation with Graph Recurrent Attention Networks
Renjie Liao
Yujia Li
Yang Song
Shenlong Wang
C. Nash
William L. Hamilton
David Duvenaud
R. Urtasun
R. Zemel
GNN
136
335
0
02 Oct 2019
Graph Residual Flow for Molecular Graph Generation
Graph Residual Flow for Molecular Graph Generation
Shion Honda
Hirotaka Akita
Katsuhiko Ishiguro
Toshiki Nakanishi
Kenta Oono
55
42
0
30 Sep 2019
Labeled Graph Generative Adversarial Networks
Labeled Graph Generative Adversarial Networks
Shuangfei Fan
Bert Huang
GAN
54
30
0
07 Jun 2019
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
Kaushalya Madhawa
Katushiko Ishiguro
Kosuke Nakago
Motoki Abe
BDL
106
192
0
28 May 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
AI4CEGNN
1.1K
5,517
0
20 Dec 2018
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation
  Models
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Daniil Polykovskiy
Alexander Zhebrak
Benjamín Sánchez-Lengeling
Sergey Golovanov
Oktai Tatanov
...
Simon Johansson
Hongming Chen
Sergey I. Nikolenko
Alán Aspuru-Guzik
Alex Zhavoronkov
ELM
259
651
0
29 Nov 2018
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph
  Generation
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation
Rim Assouel
Mohamed Ahmed
Marwin H. S. Segler
Amir Saffari
Yoshua Bengio
67
55
0
24 Nov 2018
Janossy Pooling: Learning Deep Permutation-Invariant Functions for
  Variable-Size Inputs
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
R. Murphy
Balasubramaniam Srinivasan
Vinayak A. Rao
Yun Liang
111
190
0
05 Nov 2018
Constrained Generation of Semantically Valid Graphs via Regularizing
  Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei Ma
Jie Chen
Cao Xiao
121
209
0
07 Sep 2018
Molecular generative model based on conditional variational autoencoder
  for de novo molecular design
Molecular generative model based on conditional variational autoencoder for de novo molecular design
Jaechang Lim
Seongok Ryu
Jin Woo Kim
W. Kim
BDLDRL
60
333
0
15 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph
  Generation
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
287
902
0
07 Jun 2018
Conditional molecular design with deep generative models
Conditional molecular design with deep generative models
Seokho Kang
Kyunghyun Cho
BDL
226
182
0
30 Apr 2018
Fréchet ChemNet Distance: A metric for generative models for molecules
  in drug discovery
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery
Kristina Preuer
Philipp Renz
Thomas Unterthiner
Sepp Hochreiter
Günter Klambauer
MedIm
96
338
0
26 Mar 2018
GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal
  Graphs
GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs
Jiani Zhang
Xingjian Shi
Junyuan Xie
Hao Ma
Irwin King
Dit-Yan Yeung
GNN
106
573
0
20 Mar 2018
Syntax-Directed Variational Autoencoder for Structured Data
Syntax-Directed Variational Autoencoder for Structured Data
H. Dai
Yingtao Tian
Bo Dai
Steven Skiena
Le Song
102
329
0
24 Feb 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
352
1,368
0
12 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational
  Autoencoders
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky
N. Komodakis
GNNBDL
117
850
0
09 Feb 2018
Application of generative autoencoder in de novo molecular design
Application of generative autoencoder in de novo molecular design
T. Blaschke
Marcus Olivecrona
Ola Engkvist
J. Bajorath
Hongming Chen
AI4CE
99
344
0
21 Nov 2017
Learning to Represent Programs with Graphs
Learning to Represent Programs with Graphs
Miltiadis Allamanis
Marc Brockschmidt
Mahmoud Khademi
GNNNAI
123
803
0
01 Nov 2017
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
479
20,164
0
30 Oct 2017
Deep Sets
Deep Sets
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
408
2,464
0
10 Mar 2017
Scene Graph Generation by Iterative Message Passing
Scene Graph Generation by Iterative Message Passing
Danfei Xu
Yuke Zhu
Chris Choy
Li Fei-Fei
GNN3DV
88
1,222
0
10 Jan 2017
Automatic chemical design using a data-driven continuous representation
  of molecules
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
164
2,932
0
07 Oct 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDaDiffM
301
6,949
0
12 Mar 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence
  Modeling
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung
Çağlar Gülçehre
Kyunghyun Cho
Yoshua Bengio
591
12,713
0
11 Dec 2014
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