graph representation - Robuta Search

https://openreview.net/forum?id=BIMSHniyCP Position: Relational Deep Learning - Graph Representation Learning on Relational Databases |... Much of the world's most valued data is stored in relational databases and data warehouses, where the data is organized into tables connected by... deep learning graph representation position relational databases https://mapleprimes.com/questions/144608-Converting-The-Output-Of-A-Function Converting the output of a function to a tree/graph representation - MaplePrimes the output tree graph converting https://openreview.net/forum?id=oGJFcWGePV Continuous-time Graph Representation with Sequential Survival Process | OpenReview Over the past two decades, there has been a tremendous increase in the growth of representation learning methods for graphs, with numerous applications across... continuous time graph representation sequential survival process https://deepai.org/publication/rdgsl-dynamic-graph-representation-learning-with-structure-learning RDGSL: Dynamic Graph Representation Learning with Structure Learning | DeepAI Sep 5, 2023 - 09/05/23 - Temporal Graph Networks (TGNs) have shown remarkable performance in learning representation for continuous-time dynamic graphs. Ho... graph representation learning dynamic structure deepai https://openreview.net/forum?id=OeWooOxFwDa Do Transformers Really Perform Badly for Graph Representation? | OpenReview We have explored the direct application of Transformers to graph representation. With three simple, yet effective graph structural encodings, the proposed... graph representation transformers really perform badly https://www.mdpi.com/1424-8220/22/4/1545 Graph Representation Learning-Based Early Depression Detection Framework in Smart Home Environments Although the diagnosis and treatment of depression is a medical field, ICTs and AI technologies are used widely to detect depression earlier in the elderly.... graph representation learning depression detection https://arxiv.org/abs/2406.08709 [2406.08709] Introducing Diminutive Causal Structure into Graph Representation Learning Abstract page for arXiv paper 2406.08709: Introducing Diminutive Causal Structure into Graph Representation Learning causal structure graph representation 2406 08709 introducing https://www.easychair.org/publications/preprint/TGfH Deep Graph Representation Learning for Business Process Modeling graph representation learning for business deep process modeling https://openreview.net/forum?id=X3OMHwfsxk On multi-scale Graph Representation Learning | OpenReview While Graph Neural Networks (GNNs) are widely used in modern computational biology, an underexplored drawback of common GNN methods,is that they are not... graph representation learning multi scale openreview https://aclanthology.org/2025.neusymbridge-1.2/ CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph... Jinze Sun, Yongpan Sheng, Lirong He, Yongbin Qin, Ming Liu, Tao Jia. Proceedings of Bridging Neurons and Symbols for Natural Language Processing and Knowledge... graph representation learning https://openreview.net/forum?id=1xDTDk3XPW A Large-Scale Database for Graph Representation Learning | OpenReview A large-scale graph representation learning database offering over 1.2 million graphs, averaging 15k nodes and 35k edges per graph graph representation learning large scale database openreview https://deepai.org/publication/on-minimizing-the-energy-of-a-spherical-graph-representation On Minimizing the Energy of a Spherical Graph Representation | DeepAI Sep 6, 2023 - 09/06/23 - Graph representations are the generalization of geometric graph drawings from the plane to higher dimensions. A method introduced ... the energy graph representation minimizing spherical deepai https://openreview.net/forum?id=RzwzimOPqu&referrer=%5Bthe%20profile%20of%20Bin%20Liu%5D(%2Fprofile%3Fid%3D~Bin_Liu11) Asymmetric Graph Representation Learning | OpenReview Despite the enormous success of graph neural networks (GNNs), most existing GNNs can only be applicable to undirected graphs where relationships among... graph representation learning asymmetric openreview https://www.boisestate.edu/events/tag/graph-representation-learning/ graph representation learning Archives - University Events graph representation learning archives university events https://openreview.net/forum?id=oJQWvsStNh Stable Fair Graph Representation Learning with Lipschitz Constraint | OpenReview Group fairness based on adversarial training has gained significant attention on graph data, which was implemented by masking sensitive attributes to generate... graph representation learning stable fair lipschitz constraint https://openreview.net/forum?id=OrKmTrNI-8j&referrer=%5Bthe%20profile%20of%20Ege%20%C3%96zsoy%5D(%2Fprofile%3Fid%3D~Ege_%C3%96zsoy1) Dynamic Scene Graph Representation for Surgical Video | OpenReview Surgical videos captured from microscopic or endoscopic imaging devices are rich but complex sources of information, depicting different tools and anatomical... scene graph dynamic representation surgical video https://openreview.net/forum?id=OIvg3MqWX2 A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules |... Graph neural networks (GNNs) -- learn graph representations by exploiting the graph's sparsity, connectivity, and symmetries -- have become indispensable for... rigid graph theoretically principled sparse connected https://deepai.org/publication/graph-representation-learning-for-merchant-incentive-optimization-in-mobile-payment-marketing Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing |... Feb 27, 2020 - 02/27/20 - Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is imp... graph representation learning mobile payment merchant https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.652907/full Frontiers | Graph Representation Forecasting of Patient's Medical Conditions: Toward a Digital Twin Objective Modern medicine needs to shift from a wait and react, curative discipline to a preventative, interdisciplinary science aiming at providing personal... https://arxiv.org/abs/2508.02609 [2508.02609] Entity Representation Learning Through Onsite-Offsite Graph for Pinterest Ads Abstract page for arXiv paper 2508.02609: Entity Representation Learning Through Onsite-Offsite Graph for Pinterest Ads representation learning https://openreview.net/forum?id=km9WAflDaN OPPI-GRF: Optimizing Protein-Protein Interaction Prediction with Graph-Based Representation and... Protein-protein interactions (PPIs) are essential to various biological processes, including cell signaling and metabolic regulation, making their accurate... protein interaction oppi grf optimizing https://arxiv.org/abs/2410.00665v2 [2410.00665v2] Graph-Based Representation Learning of Neuronal Dynamics and Behavior Abstract page for arXiv paper 2410.00665v2: Graph-Based Representation Learning of Neuronal Dynamics and Behavior representation learning 2410 graph based https://arxiv.org/html/2402.10409v1 Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning large language models survey paper https://pmc.ncbi.nlm.nih.gov/articles/PMC8982879/ Fast protein structure comparison through effective representation learning with contrastive graph... Protein structure alignment algorithms are often time-consuming, resulting in challenges for large-scale protein structure similarity-based retrieval. There is... protein structure comparison representation learning fast https://deepai.org/publication/gratis-deep-learning-graph-representation-with-task-specific-topology-and-multi-dimensional-edge-features GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge... Nov 19, 2022 - 11/19/22 - Graph is powerful for representing various types of real-world data. The topology (edges' presence) and edges' features of a graph... https://jmlr.org/papers/v22/19-944.html Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation laplacian matrix learning graph signals sparse https://arxiv.org/abs/2202.13013v1 [2202.13013v1] Sign and Basis Invariant Networks for Spectral Graph Representation Learning Abstract page for arXiv paper 2202.13013v1: Sign and Basis Invariant Networks for Spectral Graph Representation Learning https://openreview.net/forum?id=pe0Vdv7rsL Graph Transformers on EHRs: Better Representation Improves Downstream Performance | OpenReview Following the success of transformer-based methods across various machine learning applications, their adoption for healthcare predictive tasks using... graph transformers ehrs better representation https://www.preprints.org/manuscript/202212.0062 Motif-based Graph Representation Learning with Application to Chemical Molecules[v1] | Preprints.org This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with... graph representation learning https://arxiv.org/abs/1912.00735 [1912.00735] Using Laplacian Spectrum as Graph Feature Representation Abstract page for arXiv paper 1912.00735: Using Laplacian Spectrum as Graph Feature Representation 1912 00735 using laplacian spectrum https://arxiv.org/abs/2510.12369 [2510.12369] A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation... Abstract page for arXiv paper 2510.12369: A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation Learning https://deepai.org/publication/local-structure-aware-graph-contrastive-representation-learning Local Structure-aware Graph Contrastive Representation Learning | DeepAI Aug 7, 2023 - 08/07/23 - Traditional Graph Neural Network (GNN), as a graph representation learning method, is constrained by label information. However, G... local structure representation learning aware graph contrastive https://arxiv.org/abs/2209.03834v1 [2209.03834v1] Pre-Training a Graph Recurrent Network for Language Representation Abstract page for arXiv paper 2209.03834v1: Pre-Training a Graph Recurrent Network for Language Representation pre training for language 2209 https://aclanthology.org/2022.emnlp-main.602/ T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation - ACL Anthology Anubhav Jangra, Preksha Nema, Aravindan Raghuveer. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. 2022. https://www.kth.se/forskning/kalender/disputationer/representation-learning-and-parallelization-for-machine-learning-applications-with-graph-tabular-and-time-series-data-1.1358658 Representation Learning and Parallelization for Machine Learning Applications with Graph, Tabular,... representation learning parallelization machine applications graph https://www.kth.se/om/upptack/kalender/representation-learning-and-parallelization-for-machine-learning-applications-with-graph-tabular-and-time-series-data-1.1358658?date=2024-10-21&orgdate=2024-10-10&length=1&orglength=0 Representation Learning and Parallelization for Machine Learning Applications with Graph, Tabular,... representation learning parallelization machine applications graph https://openreview.net/forum?id=6VuTXirQIv&referrer=%5Bthe%20profile%20of%20Sandeep%20Kumar%5D(%2Fprofile%3Fid%3D~Sandeep_Kumar8) Feature Driven Graph Coarsening for Scaling Graph Representation Learning | OpenReview Graphical modelling for structured data analysis has gained prominence across numerous domains. A significant computational challenge lies in efficiently... representation learning feature driven graph scaling https://pmc.ncbi.nlm.nih.gov/articles/PMC10204317/ Graph construction method impacts variation representation and analyses in a bovine super-pangenome... Several models and algorithms have been proposed to build pangenomes from multiple input assemblies, but their impact on variant representation, and... https://deepai.org/publication/object-structural-points-representation-for-graph-based-semantic-monocular-localization-and-mapping Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping... Jun 21, 2022 - 06/21/22 - Efficient object level representation for monocular semantic simultaneous localization and mapping (SLAM) still lacks a widely acc... https://arxiv.org/abs/2505.05461 [2505.05461] Representation Stability for Marked Graph Complexes Abstract page for arXiv paper 2505.05461: Representation Stability for Marked Graph Complexes marked graph 2505 05461 representation stability https://openreview.net/forum?id=AXWygMvuT6Q Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph | OpenReview This paper addresses the unsupervised learning of content-style decomposed representation. We first give a definition of style and then model the content-style... learning content https://pmc.ncbi.nlm.nih.gov/articles/PMC9932324/ Detection of autism spectrum disorder using graph representation learning algorithms and deep... Can we apply graph representation learning algorithms to identify autism spectrum disorder (ASD) patients within a large brain imaging dataset? ASD is mainly... autism spectrum disorder graph representation learning https://arxiv.org/abs/2403.01563 [2403.01563] The $k$-representation number of the random graph Abstract page for arXiv paper 2403.01563: The $k$-representation number of the random graph the k 2403 01563 representation number https://openreview.net/forum?id=pTmYjQadg9 Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning | OpenReview We propose a variational autoencoder that encodes graphs in a fixed-size latent space that is invariant under permutation of the input graph. variational autoencoder representation learning permutation invariant graph