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 631–640 of 712 papers

TitleStatusHype
Mapping High-level Semantic Regions in Indoor Environments without Object Recognition—0
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction—0
MaterioMiner -- An ontology-based text mining dataset for extraction of process-structure-property entities—0
Meta Spatio-Temporal Debiasing for Video Scene Graph Generation—0
Metric-Semantic Factor Graph Generation based on Graph Neural Networks—0
MG-SAGC: A multiscale graph and its self-adaptive graph convolution network for 3D point clouds—0
MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation—0
Mitigating Graph Covariate Shift via Score-based Out-of-distribution Augmentation—0
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition—0
MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis—0
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Benchmark Results

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