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20092023
most citedDropEdge: Towards Deep Graph Convolutional Networks on Node Classification

649 citations · 4.6k across the 115 of their papers we have counts for

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Showing 2022Show all

17 papers · 1 filter

cs.CV2022

Hierarchical Transformer for Survival Prediction Using Multimodality Whole Slide Images and Genomics

Chunyuan Li, Xinliang Zhu, Jiawen Yao +1

Learning good representation of giga-pixel level whole slide pathology images (WSI) for downstream tasks is critical. Previous studies employ multiple instance learning (MIL) to re…

cs.LG2022

Pareto-aware Neural Architecture Generation for Diverse Computational Budgets

Yong Guo, Yaofo Chen, Yin Zheng +5

Designing feasible and effective architectures under diverse computational budgets, incurred by different applications/devices, is essential for deploying deep models in real-world…

cs.LG2022★ 10 cited

MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction

Jiahan Liu, Chaochao Yan, Yang Yu +4

Retrosynthesis is a major task for drug discovery. It is formulated as a graph-generating problem by many existing approaches. Specifically, these methods firstly identify the reac…

eess.IV2022★ 2 cited

DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep Learning

Sen Yang, Tao Shen, Yuqi Fang +5

The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field. However, a persistent issue remains unsolv…

cs.CV2022★ 1 cited

ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images

Jiawei Yang, Hanbo Chen, Yuan Liang +3

Detectingandsegmentingobjectswithinwholeslideimagesis essential in computational pathology workflow. Self-supervised learning (SSL) is appealing to such annotation-heavy tasks. Des…

cs.LG2022

Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training

Xueyi Liu, Yu Rong, Tingyang Xu +3

Graph instance contrastive learning has been proved as an effective task for Graph Neural Network (GNN) pre-training. However, one key issue may seriously impede the representative…