v0.5.0

GAMMA Lab officially released version 0.5 of GammaGL today. You can download the latest GammaGL from the OpenI community, Github, or through pip.

Highlights

• Implemented interfaces for GraphStore and FeatureStore, and provided an example of training GraphSAGE using the Reddit dataset. #215
• The segment operator now supports data inputs of types float16, float64, and int. #197
• Implemented the bspmm operator, achieving a performance improvement of 2.3X compared to previous methods. #210
• Improved the invocation of the spmm and bspmm operators, allowing users to simply implement the message_aggregate method in convolution layers. #216
• Support for sampling under CUDA. #209
• Use of a unified extension interface for project compilation. #219

New Additions

• Add Hid-Net, a general diffusion equation framework with fidelity terms [AAAI 2023] #202
• Add FusedGAT, a graph neural network model optimized from computation, IO, and memory aspects [MLSys 2022] #195
• Add GLNN, a graph neural network model combining GNN and MLP through knowledge distillation [ICLR 2022] #205
• Add GNNLF-HF, a graph neural network model revealing essential links between different GNN propagation mechanisms [WWW 2021] #9f86d5e
• Add Sp2GCL, a graph contrastive learning framework integrating spatial and spectral views [NeurIPS 2023] #201
• Add DFAD-GNN, a data-free adversarial knowledge distillation graph neural network model [IJCAI 2022] #212
• Add HEAT, a trajectory prediction framework for heterogeneous traffic participants [T-ITS 2022] #206
• Add HeCo, a self-supervised heterogeneous graph neural network contrastive learning framework [KDD 2021] #204
• Add DHN, a distance encoding technique to enhance the expressive power of heterogeneous graph neural networks [TKDE 2023] #207
• Add DNA, an attention-based dynamic neighborhood aggregation method for graph representation learning [ICLR 2019] #214
• Add homogeneous graph datasets: Facebook (#201) and Yelp (#5c7ccfe)
• Add heterogeneous graph datasets: ACM4DHN and ACM4HeCo #204
• Add NGSIM dataset for traffic simulation #d741516
• Add SVDFeatureReduction, an SVD method for feature decomposition #6ddba3a
• Add get_train_val_test_split, a new interface for dataset partitioning #080b4d5
• Add dataset partitioning fields to the Amazon dataset #dc0511c

Bugs

• Fix repeated definition issue of forward dropout in MLP #2403822
• Fix calculation errors of the segment_mean operator in CUDA environments #fb00d7f
• Fix efficiency issues with the get_laplacian utility class when computing on large graphs #201