CHEN SHENGYUAN — accepted AI-conference papers

2023

Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs

CHEN SHENGYUAN, YUNFENG CAI, Huang Fang, Xiao Huang, Mingming Sun

NeurIPS 2023poster

Knowledge graph (KG) reasoning utilizes two primary techniques, i.e., rule-based and KG-embedding based. The former provides precise inferences, but inferring via concrete rules is not scalable. The latter enables efficient reasoning at the cost of ambiguous inference accuracy. Neuro-symbolic reason…

Cited by 25 Source ↗PDF ↗Scholar ↗

2023

RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations

Zirui Liu, CHEN SHENGYUAN, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu

ICML 2023poster

Training graph neural networks (GNNs) is extremely time consuming because sparse graph-based operations are hard to be accelerated by community hardware. Prior art successfully reduces the computation cost of dense matrix based operations (e.g., convolution and linear) via sampling-based approximati…

Cited by 28 Source ↗PDF ↗Scholar ↗