232 citations · 1.4k across the 72 of their papers we have counts for
12 papers · 1 filter
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
Deoscillated Graph Collaborative Filtering
Zhiwei Liu, Lin Meng, Fei Jiang +2
Collaborative Filtering (CF) signals are crucial for a Recommender System~(RS) model to learn user and item embeddings. High-order information can alleviate the cold-start issue of…
Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning
Yizhu Jiao, Yun Xiong, Jiawei Zhang +3
Graph representation learning has attracted lots of attention recently. Existing graph neural networks fed with the complete graph data are not scalable due to limited computation…
G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning
Jiawei Zhang
The recent GRAPH-BERT model introduces a new approach to learning graph representations merely based on the attention mechanism. GRAPH-BERT provides an opportunity for transferring…
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo +1
Non-local self-similarity in natural images has been well studied as an effective prior in image restoration. However, for single image super-resolution (SISR), most existing deep…
CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection
Congying Xia, Chenwei Zhang, Hoang Nguyen +2
In this paper, we formulate a more realistic and difficult problem setup for the intent detection task in natural language understanding, namely Generalized Few-Shot Intent Detecti…
Graph Neural Distance Metric Learning with Graph-Bert
Jiawei Zhang
Graph distance metric learning serves as the foundation for many graph learning problems, e.g., graph clustering, graph classification and graph matching. Existing research works o…
Segmented Graph-Bert for Graph Instance Modeling
Jiawei Zhang
In graph instance representation learning, both the diverse graph instance sizes and the graph node orderless property have been the major obstacles that render existing representa…
Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network
Jiyang Bai, Yuxiang Ren, Jiawei Zhang
Graph neural networks (GNNs) have achieved outstanding performance in learning graph-structured data and various tasks. However, many current GNNs suffer from three common problems…
Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention
Yuxiang Ren, Jiawei Zhang
The viral spread of fake news has caused great social harm, making fake news detection an urgent task. Current fake news detection methods rely heavily on text information by learn…
Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised Classification
Jiawei Zhang
Existing graph neural networks may suffer from the "suspended animation problem" when the model architecture goes deep. Meanwhile, for some graph learning scenarios, e.g., nodes wi…
Graph-Bert: Only Attention is Needed for Learning Graph Representations
Jiawei Zhang, Haopeng Zhang, Congying Xia +1
The dominant graph neural networks (GNNs) over-rely on the graph links, several serious performance problems with which have been witnessed already, e.g., suspended animation probl…