16 citations · 54 across the 20 of their papers we have counts for
7 papers · 1 filter
Faith: An Efficient Framework for Transformer Verification on GPUs
Boyuan Feng, Tianqi Tang, Yuke Wang +5
Transformer verification draws increasing attention in machine learning research and industry. It formally verifies the robustness of transformers against adversarial attacks such…
TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs
Yuke Wang, Boyuan Feng, Zheng Wang +2
Recently, graph neural networks (GNNs), as the backbone of graph-based machine learning, demonstrate great success in various domains (e.g., e-commerce). However, the performance o…
DSXplore: Optimizing Convolutional Neural Networks via Sliding-Channel Convolutions
Yuke Wang, Boyuan Feng, Yufei Ding
As the key advancement of the convolutional neural networks (CNNs), depthwise separable convolutions (DSCs) are becoming one of the most popular techniques to reduce the computatio…
Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks
Boyuan Feng, Yuke Wang, Zheng Wang +1
With the increasing popularity of graph-based learning, graph neural networks (GNNs) emerge as the essential tool for gaining insights from graphs. However, unlike the conventional…
Scalable Adversarial Attack on Graph Neural Networks with Alternating Direction Method of Multipliers
Boyuan Feng, Yuke Wang, Xu Li +1
Graph neural networks (GNNs) have achieved high performance in analyzing graph-structured data and have been widely deployed in safety-critical areas, such as finance and autonomou…
SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization
Boyuan Feng, Yuke Wang, Xu Li +3
With the increasing popularity of graph-based learning, Graph Neural Networks (GNNs) win lots of attention from the research and industry field because of their high accuracy. Howe…
Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of Compounds
Lingwei Xie, Song He, Shu Yang +5
With the rapid development of high-throughput technologies, parallel acquisition of large-scale drug-informatics data provides huge opportunities to improve pharmaceutical research…