# Graph Generation

100 papers with code • 1 benchmarks • 5 datasets

Graph Generation is an important research area with significant applications in drug and material designs.

# Scalable Deep Generative Modeling for Sparse Graphs

Based on this, we develop a novel autoregressive model, named BiGG, that utilizes this sparsity to avoid generating the full adjacency matrix, and importantly reduces the graph generation time complexity to $O((n + m)\log n)$.

20,702

# WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset

We present a new dataset of Wikipedia articles each paired with a knowledge graph, to facilitate the research in conditional text generation, graph generation and graph representation learning.

8,972

# Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.

1,192

# DIG: A Turnkey Library for Diving into Graph Deep Learning Research

23 Mar 2021

Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning.

967

# GraphEBM: Molecular Graph Generation with Energy-Based Models

We note that most existing approaches for molecular graph generation fail to guarantee the intrinsic property of permutation invariance, resulting in unexpected bias in generative models.

967

# Graph R-CNN for Scene Graph Generation

We propose a novel scene graph generation model called Graph R-CNN, that is both effective and efficient at detecting objects and their relations in images.

632

# Unbiased Scene Graph Generation from Biased Training

Today's scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e. g., collapsing diverse "human walk on / sit on / lay on beach" into "human on beach".

626

# Learning to Compose Dynamic Tree Structures for Visual Contexts

We propose to compose dynamic tree structures that place the objects in an image into a visual context, helping visual reasoning tasks such as scene graph generation and visual Q&A.

626

# Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations

We provide a new graph generator, based on a "forest fire" spreading process, that has a simple, intuitive justification, requires very few parameters (like the "flammability" of nodes), and produces graphs exhibiting the full range of properties observed both in prior work and in the present study.

570

# GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

28 May 2019

We propose GraphNVP, the first invertible, normalizing flow-based molecular graph generation model.

513