2024 Interpretable and efficient heterogeneous

Interpretable and efficient heterogeneous

Author: ponh

August undefined, 2024

WebTo address the above issues, we propose an interpretable and efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn the representations of objects in HINs. … WebJan 15, 2024 · A new model to address challenges in scalability, model interpretability, and confounders of computational single-cell RNA-seq analyses is shown, by learning meaningful embeddings from the data that simultaneously refine gene signatures and cell functions in diverse conditions. The advent of single-cell RNA sequencing (scRNA-seq) …

Interpretable and Efficient Heterogeneous Graph …

Web@article{yang2024interpretable, title={Interpretable and efficient heterogeneous graph convolutional network}, author={Yang, Yaming and Guan, Ziyu and Li, Jianxin and Zhao, … WebDec 26, 2024 · We consider the task of meta-analysis in high-dimensional settings in which the data sources are similar but non-identical. To borrow strength across such heterogeneous datasets, we introduce a global parameter that emphasizes interpretability and statistical efficiency in the presence of heterogeneity. We also propose a one-shot … sunday lunch at leeds castle

Interpretable Recommender System With Heterogeneous …

WebFig. 4. Classification performance of ie-HGCN w.r.t. the hidden layer dimensionality da of the type-level attention. - "Interpretable and Efficient Heterogeneous Graph Convolutional … WebMay 27, 2024 · Fig. 2. The overall architecture of ie-HGCN on DBLP. (a): An instance of ie-HGCN with 5 layers. The solid lines stand for the relation-specific projection, and the … WebInterpretable Relation Learning on Heterogeneous Graphs. Pages 1266 ... which both consider the semantics of nodes in the heterogeneous graph. ... Richang Hong, Yanjie … sunday log sheet

(PDF) Interpretable and Personalized Apprenticeship Scheduling ...

Combining Heterogeneous Vehicles to Build a Low-Cost and Real …

WebHere, we present IGSimpute, an accurate and interpretable imputation method for recovering missing values in scRNA-seq data with an interpretable instance-wise gene selection layer (GSL). IGSimpute outperforms 12 other state-of-the-art imputation methods on 13 out of 17 datasets from different scRNA-seq technologies with the lowest mean … WebJan 31, 2024 · A wireless charging system that supports a large sensor network not only needs to provide real-time charging services but also needs to consider the cost of construction in order to meet the actual applications and considerations. The energy transfer between mobile devices is extremely difficult, especially at large distances, while at close … palm beach state state collegeWebApr 12, 2024 · Accuracy and interpretability are two essential properties for a crime prediction model. ... Heterogeneous information network embedding for estimating time of arrival. In Proceedings of KDD. ... Efficient scheduling of … sunday lunch at the gravy boat 11 november

"Web1 day ago · According to NIST, “trustworthy AI” systems are, among other things, “valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with their harmful bias managed.” Along the same lines, the Blueprint identifies a set of five principles and associated practices to help … " - Interpretable and efficient heterogeneous

Interpretable and efficient heterogeneous

WebEconML: A Python Package for ML-Based Heterogeneous Treatment Effects Estimation. EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal to combine state-of-the-art machine … WebJun 8, 2024 · We build interpretable policies that maximize efficiency while ensuring fairness across NST scores (see Introduction) and across races, in turn. We use real-world data (10,922 homeless youth and 3474 housing resources) from the HMIS database obtained from Ian De Jong as part of a working group called “Youth Homelessness Data, …

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WebAug 6, 2024 · To address the above issues, we propose an interpretable and efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn the representations of … WebFig. 4. Classification performance of ie-HGCN w.r.t. the hidden layer dimensionality da of the type-level attention. - "Interpretable and Efficient Heterogeneous Graph Convolutional Network"

WebDec 21, 2024 · Yang et al. proposed an Interpretable and Efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn heterogeneous graph embedding by using a … WebJan 1, 2024 · The proposed model is easy to implement and efficient to optimize and is shown to outperform state-of-the-art top-N recommendation methods that use side information. Read more Preprint

WebMar 17, 2024 · Abstract. Most applications of machine learning in heterogeneous catalysis thus far have used black-box models to predict computable physical properties (descriptors), such as adsorption or ... WebMar 17, 2024 · Most applications of machine learning in heterogeneous catalysis thus far have used black-box models to predict computable physical properties (descriptors), such as adsorption or formation ...

WebMar 17, 2024 · Most applications of machine learning in heterogeneous catalysis thus far have used black-box models to predict computable physical properties (descriptors), … sunday lunch at the crown stoke by naylandWebJun 14, 2024 · To perform this job, domain experts leverage heterogeneous strategies and rules-of-thumb honed over years of apprenticeship. What is critically needed is the ability to extract this domain knowledge in a heterogeneous and interpretable apprenticeship learning framework to scale beyond the power of a single human expert, a necessity in … palm beach state summer 2023 coursesWebApr 14, 2024 · In this study, we introduce an interpretable graph-based deep learning prediction model, AttentionSiteDTI, which utilizes protein binding sites along with a self-attention mechanism to address the ... sunday love songs steve wrightWebDec 10, 2024 · SAFRAN yields new state-of-the-art results for fully interpretable link prediction on the established general-purpose benchmark FB15K-237 and the large-scale biomedical benchmark OpenBioLink. Furthermore, it exceeds the results of multiple established embedding-based algorithms on FB15K-237 and narrows the gap between … sunday long live radioWebGraph Convolutional Network (GCN) has achieved extraordinary success in learning effective task-specific representations of nodes in graphs. However, regarding Heterogeneous Information Network (HIN), existing HIN-orie… palm beach state transferWebTo address the above issues, we propose interpretable and efﬁcient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn representations of nodes in HINs. It automatically extracts useful meta-paths for each node from all possible meta-paths (within a length limit determined by the model depth), which brings good model interpretability. palm beach state spring breakWebApr 13, 2024 · Overlay design. One of the key aspects of coping with dynamic and heterogeneous p2p network topologies is the overlay design, which defines how nodes are organized and connected in the logical ... sunday lunch alternatives