LAUSR

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Sign Up to like & get
recommendations!
1 Published in 2019 at "Chemistry of Materials"

DOI: 10.1021/acs.chemmater.9b01294

Abstract: Graph networks are a new machine learning (ML) paradigm that supports both relational reasoning and combinatorial generalization. Here, we develop, for the first time, universal MatErials Graph Network (MEGNet) models for accurate property prediction in… read more here.

Keywords: machine learning; molecules crystals; megnet models; graph networks ... See more keywords

Learning self-driven collective dynamics with graph networks

Sign Up to like & get
recommendations!
1 Published in 2022 at "Scientific Reports"

DOI: 10.1038/s41598-021-04456-5

Abstract: Despite decades of theoretical research, the nature of the self-driven collective motion remains indigestible and controversial, while the phase transition process of its dynamic is a major research issue. Recent methods propose to infer the… read more here.

Keywords: self driven; learning self; graph networks; driven collective ... See more keywords

Explaining Deep Graph Networks via Input Perturbation.

Sign Up to like & get
recommendations!
3 Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3165618

Abstract: Deep graph networks (DGNs) are a family of machine learning models for structured data which are finding heavy application in life sciences (drug repurposing, molecular property predictions) and on social network data (recommendation systems). The… read more here.

Keywords: deep graph; via input; networks via; explaining deep ... See more keywords

Uniform Pooling for Graph Networks

Sign Up to like & get
recommendations!
1 Published in 2020 at "Applied Sciences"

DOI: 10.3390/app10186287

Abstract: The graph convolution network has received a lot of attention because it extends the convolution to non-Euclidean domains. However, the graph pooling method is still less concerned, which can learn coarse graph embedding to facilitate… read more here.

Keywords: pooling graph; uniform pooling; graph; convolution ... See more keywords

Discourse-Aware Graph Networks for Textual Logical Reasoning

Sign Up to like & get
recommendations!
1 Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"

DOI: 10.48550/arxiv.2207.01450

Abstract: Textual logical reasoning, especially question-answering (QA) tasks with logical reasoning, requires awareness of particular logical structures. The passage-level logical relations represent entailment or contradiction between propositional units (e.g., a concluding sentence). However, such structures are… read more here.

Keywords: discourse aware; aware graph; logical reasoning; textual logical ... See more keywords