SOTAVerified

Graph Generation

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

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–410 of 712 papers

TitleStatusHype
Gradient-Guided Importance Sampling for Learning Binary Energy-Based ModelsCode0
A Framework for Large Scale Synthetic Graph Dataset Generation—0
Unbiased Scene Graph Generation using Predicate Similarities—0
Benchmark for Research Theme Classification of Scholarly DocumentsCode0
Overview of the Third Workshop on Scholarly Document Processing—0
DiGress: Discrete Denoising diffusion for graph generationCode2
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction—0
Face Super-Resolution Using Stochastic Differential EquationsCode1
SCGG: A Deep Structure-Conditioned Graph Generative Model—0
Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity—0
Show:102550
← PrevPage 41 of 72Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified