37 citations · 58 across the 3 of their papers we have counts for
9 papers
Multi-task Learning of Order-Consistent Causal Graphs
Xinshi Chen, Haoran Sun, Caleb Ellington +2
We consider the problem of discovering related Gaussian directed acyclic graphs (DAGs), where the involved graph structures share a consistent causal order and sparse unions of…
Learning to Stop While Learning to Predict
Xinshi Chen, Hanjun Dai, Yu Li +2
There is a recent surge of interest in designing deep architectures based on the update steps in traditional algorithms, or learning neural networks to improve and replace traditio…
Understanding Deep Architectures with Reasoning Layer
Xinshi Chen, Yufei Zhang, Christoph Reisinger +1
Recently, there has been a surge of interest in combining deep learning models with reasoning in order to handle more sophisticated learning tasks. In many cases, a reasoning task…
RNA Secondary Structure Prediction By Learning Unrolled Algorithms
Xinshi Chen, Yu Li, Ramzan Umarov +2
In this paper, we propose an end-to-end deep learning model, called E2Efold, for RNA secondary structure prediction which can effectively take into account the inherent constraints…
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Yuyu Zhang, Xinshi Chen, Yuan Yang +4
Markov Logic Networks (MLNs), which elegantly combine logic rules and probabilistic graphical models, can be used to address many knowledge graph problems. However, inference in ML…
Can Graph Neural Networks Help Logic Reasoning?
Yuyu Zhang, Xinshi Chen, Yuan Yang +4
Effectively combining logic reasoning and probabilistic inference has been a long-standing goal of machine learning: the former has the ability to generalize with small training da…