53 citations · 113 across the 14 of their papers we have counts for
6 papers · 1 filter
Graph Neural Reasoning May Fail in Certifying Boolean Unsatisfiability
Ziliang Chen, Zhanfu Yang
It is feasible and practically-valuable to bridge the characteristics between graph neural networks (GNNs) and logical reasoning. Despite considerable efforts and successes witness…
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning
Xiaopeng Yan, Ziliang Chen, Anni Xu +3
Resembling the rapid learning capability of human, few-shot learning empowers vision systems to understand new concepts by training with few samples. Leading approaches derived fro…
Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching
Ziliang Chen, Zhanfu Yang, Xiaoxi Wang +4
A broad range of cross--domain generation researches boil down to matching a joint distribution by deep generative models (DGMs). Hitherto algorithms excel in pairwise domains w…
Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks
Ziliang Chen, Jingyu Zhuang, Xiaodan Liang +1
(Unsupervised) Domain Adaptation (DA) seeks for classifying target instances when solely provided with source labeled and target unlabeled examples for training. Learning domain-in…
Graph Neural Reasoning for 2-Quantified Boolean Formula Solvers
Zhanfu Yang, Fei Wang, Ziliang Chen +2
In this paper, we investigate the feasibility of learning GNN (Graph Neural Network) based solvers and GNN-based heuristics for specified QBF (Quantified Boolean Formula) problems.…
FRAME Revisited: An Interpretation View Based on Particle Evolution
Xu Cai, Yang Wu, Guanbin Li +2
FRAME (Filters, Random fields, And Maximum Entropy) is an energy-based descriptive model that synthesizes visual realism by capturing mutual patterns from structural input signals.…