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https://ar5iv.labs.arxiv.org/html/2503.11900 [2503.11900] Heterogenous graph neural networks for species distribution modeling Species distribution models (SDMs) are necessary for measuring and predicting occurrences and habitat suitability of species and their relationship with... graph neural networks species distribution modeling https://openreview.net/forum?id=r1lZ7AEKvB The Logical Expressiveness of Graph Neural Networks | OpenReview We characterize the expressive power of GNNs in terms of classical logical languages, separating different GNNs and showing connections with standard notions... graph neural networks logical expressiveness openreview https://pubmed.ncbi.nlm.nih.gov/35671364/?dopt=Abstract&holding=idemdclib_fft&otool=idemdclib Graph Neural Networks for Learning Molecular Excitation Spectra Machine learning (ML) approaches have demonstrated the ability to predict molecular spectra at a fraction of the computational cost of traditional theoretical... graph neural networks for learning molecular excitation spectra https://uu.diva-portal.org/smash/record.jsf?pid=diva2%3A1744983 Graph Neural Networks for low-energy event classification & reconstruction in IceCube graph neural networks low energy https://arxiv.org/abs/2111.10657v4 [2111.10657v4] Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Abstract page for arXiv paper 2111.10657v4: Generalizing Graph Neural Networks on Out-Of-Distribution Graphs graph neural networks out of https://pmc.ncbi.nlm.nih.gov/articles/PMC8360394/ Graph Neural Networks and Their Current Applications in Bioinformatics - PMC Graph neural networks (GNNs), as a branch of deep learning in non-Euclidean space, perform particularly well in various tasks that process graph structure... graph neural networks current applications bioinformatics pmc https://research.nvidia.com/index.php/publication/2023-11_graph-neural-networks-enhanced-decoding-quantum-ldpc-codes Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes | Research In this work, we propose a fully differentiable iterative decoder for quantum low-density parity-check (LDPC) codes. The proposed algorithm is composed of... graph neural networks enhanced https://www.mis.mpg.de/de/events/series/graph-neural-networks-mini-meeting-at-mpi-mis Graph Neural Networks Mini Meeting at MPI MiS: MPI MIS graph neural networks mini meeting mpi mis https://research.google/pubs/heterogenous-graph-neural-networks-for-species-distribution-modeling/ Heterogeneous graph neural networks for species distribution modeling graph neural networks species distribution heterogeneous modeling https://par.nsf.gov/biblio/10639245-memfreezing-novel-adversarial-attack-temporal-graph-neural-networks-under-limited-future-knowledge MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future... This page contains metadata information for the record with PAR ID 10639245 graph neural networks https://panford.github.io/publication/bitrade Bilateral Trade Modelling with Graph Neural Networks - Kobby Panford-Quainoo Jan 1, 2020 - This paper is about the number 2. The number 3 is left for future work. graph neural networks bilateral trade modelling https://www.cs.cit.tum.de/en/sccs/news/news/article/oliver-beck-sampling-weights-of-graph-neural-networks/ Oliver Beck: Sampling weights of Graph Neural Networks - Chair of Scientific Computing graph neural networks oliver beck sampling weights https://rescience.github.io/bibliography/Mahlau_2023.html [Re] On Explainability of Graph Neural Networks via Subgraph Explorations graph neural networks explainability via subgraph explorations https://doyle.chem.ucla.edu/multi-level-qtaim-enriched-graph-neural-networks-for-resolving-properties-of-transition-metal-complexes/ Multi-level QTAIM-Enriched Graph Neural Networks for Resolving Properties of Transition Metal... Congratulations to Winston on his publication! graph neural networks https://impact.ornl.gov/en/publications/extensive-attention-mechanisms-in-graph-neural-networks-for-mater/ Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery - Oak Ridge... graph neural networks attention mechanisms https://conservancy.umn.edu/items/756a09c1-a3c4-4d62-8460-4731c58e35f6 Towards Learning Powerful Deep Graph Neural Networks and Embeddings Learning powerful data embeddings has recently become the core of machine learning algorithms especially in natural language processing and computer vision... graph neural networks towards learning powerful deep https://www.kellogg.northwestern.edu/academics-research/research/detail/2021/meta-learning-with-graph-neural-networks-methods-and-applications/ Meta-Learning with Graph Neural Networks: Methods and Applications | Kellogg School of Management Graph Neural Networks (GNNs), a generalization of deep neural networks on graph data have been widely used in various domains, ranging from drug discovery to... graph neural networks https://resources.nvidia.com/en-us-financial-service/en-us-financial-services-industry/optimizing-fraud-det?xs=467098 Optimizing Fraud Detection in Financial Services with Graph Neural Networks and NVIDIA GPUs Learn an end-to-end workflow showcasing best practices for detecting financial services fraud using GNNs and GPUs. graph neural networks https://intra.kth.se/en/eecs/kalender/on-the-adversarial-robustness-of-graph-neural-networks-1.1466748?date=2026-04-23&orgdate=2026-03-09&length=1&orglength=298 On the Adversarial Robustness of Graph Neural Networks | EECS internal pages graph neural networks on the adversarial robustness https://www.ijcai.org/proceedings/2021/291 The Surprising Power of Graph Neural Networks with Random Node Initialization | IJCAI Electronic proceedings of IJCAI 2021 graph neural networks power of https://research.tudelft.nl/en/datasets/data-for-paper-evaluation-of-graph-neural-networks-for-urban-drai/publications/ Data for paper "Evaluation of Graph Neural Networks for Urban Drainage Metamodeling: Key Components... graph neural networks https://experts.umn.edu/en/publications/rsc-accelerate-graph-neural-networks-training-via-randomized-spar/ RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations -... graph neural networks rsc accelerate training via https://publikationen.bibliothek.kit.edu/1000156224 Graph Neural Networks for low-energy event classification & re... graph neural networks low energy event classification https://par.nsf.gov/biblio/10633159-towards-expressive-spectral-temporal-graph-neural-networks-time-series-forecasting Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting | NSF Public... This page contains metadata information for the record with PAR ID 10633159 graph neural networks https://researchdiscovery.drexel.edu/esploro/outputs/doctoral/Graph-neural-networks-for-3D-shape/991021890111904721 Graph neural networks for 3D shape analysis - Drexel University Deep learning on 3D meshes presents significant challenges due to their intricate and non-uniform structure. Traditional deep learning methods, which are... graph neural networks shape analysis drexel university https://arxiv.org/abs/1902.08412 [1902.08412] Adversarial Attacks on Graph Neural Networks via Meta Learning Abstract page for arXiv paper 1902.08412: Adversarial Attacks on Graph Neural Networks via Meta Learning graph neural networks adversarial attacks https://scholars.duke.edu/publication/1634002 Scholars@Duke publication: Linear-Time Graph Neural Networks for Scalable Recommendations graph neural networks scholars duke publication linear https://intra.kth.se/en/aktuellt/kalender/on-the-adversarial-robustness-of-graph-neural-networks-1.1466748?date=2026-04-23&orgdate=2026-04-21&length=1&orglength=0 On the Adversarial Robustness of Graph Neural Networks | KTH graph neural networks on the adversarial robustness kth https://arxiv.org/abs/2212.09034v4 [2212.09034v4] Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs... Abstract page for arXiv paper 2212.09034v4: Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs graph neural networks https://arxiv.org/abs/2209.14107v1 [2209.14107v1] Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure Abstract page for arXiv paper 2209.14107v1: Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure graph neural networks https://arxiv.org/abs/2112.06538 [2112.06538] Hybrid Graph Neural Networks for Few-Shot Learning Abstract page for arXiv paper 2112.06538: Hybrid Graph Neural Networks for Few-Shot Learning graph neural networks hybrid shot learning https://resources.nvidia.com/en-us-financial-services-industry/optimizing-fraud-det?xs=467098 Optimizing Fraud Detection in Financial Services with Graph Neural Networks and NVIDIA GPUs Learn an end-to-end workflow showcasing best practices for detecting financial services fraud using GNNs and GPUs. graph neural networks https://nhess.copernicus.org/articles/25/335/2025/nhess-25-335-2025-metrics.html NHESS - Metrics - Multi-scale hydraulic graph neural networks for flood modelling Abstract. Deep-learning-based surrogate models represent a powerful alternative to numerical models for speeding up flood mapping while preserving accuracy. In... graph neural networks multi scale nhess metrics hydraulic https://arxiv.org/abs/2201.01855v1 [2201.01855v1] Graph Neural Networks for Double-Strand DNA Breaks Prediction Abstract page for arXiv paper 2201.01855v1: Graph Neural Networks for Double-Strand DNA Breaks Prediction graph neural networks double strand https://research.facebook.com/publications/multi-channel-speech-enhancement-using-graph-neural-networks/ Multi-Channel Speech Enhancement Using Graph Neural Networks - Meta Research In this paper, we introduce a different research direction by viewing each audio channel as a node lying in a non-Euclidean space and, specifically, a graph. graph neural networks multi channel speech enhancement using meta https://scholars.duke.edu/publication/1530601 Scholars@Duke publication: Permutation-Equivariant and Proximity-Aware Graph Neural Networks With... graph neural networks https://arxiv.org/abs/2506.12700 [2506.12700] Large Scalable Cross-Domain Graph Neural Networks for Personalized Notification at... Abstract page for arXiv paper 2506.12700: Large Scalable Cross-Domain Graph Neural Networks for Personalized Notification at LinkedIn graph neural networks https://indico.cern.ch/event/1128328/contributions/4900731/ Mini-workshop on Graph Neural Networks for Tracking (June 3, 2022): Accelerated Graph Neural... Graph networks show great promise for HEP tracking on detectors ranging from silicon trackers to LAr TPCs. As the demonstrators are applied to increasingly... graph neural networks mini workshop https://portal.fis.tum.de/en/publications/graph-neural-networks-as-strategic-transport-modelling-alternativ/ Graph neural networks as strategic transport modelling alternative - A proof of concept for a... graph neural networks https://research.ibm.com/publications/communication-efficient-graph-neural-networks-with-probabilistic-neighborhood-expansion-analysis-and-caching Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis... Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching for MLSys 2023 by Tim Kaler et al. graph neural networks communication efficient probabilistic neighborhood https://iris.cnr.it/handle/20.500.14243/457525 GNOSIS: proactive image placement using graph neural networks & deep reinforcement learning graph neural networks gnosis proactive image placement https://gnn.seas.upenn.edu/ Graph Neural Networks – ESE 5140 graph neural networks ese https://www.research.autodesk.com/publications/leveraging-graph-neural-networks-for-graph-regression-and-effective-enumeration-reduction/ Leveraging Graph Neural Networks for Graph Regression and Effective Enumeration Reduction Apr 29, 2025 - Graph-based framework represents aspects of optimal thermal management system design to rapidly and efficiently identify optimal design candidates. graph neural networks leveraging regression effective enumeration https://blogs.nvidia.com/blog/what-are-graph-neural-networks/?nv_excludes=60387,60390 What Are Graph Neural Networks? | NVIDIA Blogs Nov 1, 2022 - Graph neural networks (GNNs) apply the predictive power of deep learning to rich data structures that depict objects and their relationships as points... graph neural networks nvidia blogs https://pubmed.ncbi.nlm.nih.gov/37925203/?otool=flbhsflib&holding=flbhsflib Graph neural networks in EEG spike detection This study opens the door for the discovery of the powerful role played by GNNs in capturing IEDs, which is an essential step for identifying the epileptogenic... graph neural networks eeg spike detection https://podcasts.ox.ac.uk/index.php/introduction-deep-learning-and-graph-neural-networks-biomedicine?video=1 Introduction to Deep Learning and Graph Neural Networks in Biomedicine | University of Oxford... introduction to deep learning graph neural networks https://math.asu.edu/node/9080 Directed Graph Neural Networks for Ranking and Angular Synchronization | School of Mathematical and... CAM/DoMSS SeminarMonday, September 301:30pm MST/AZWXLR A304 graph neural networks https://ieeetv.ieee.org/ondemand/ieee-icassp-2020-virtual-conference-may-2020/6146/optimal-power-flow-using-graph-neural-networks Optimal Power Flow Using Graph Neural Networks | IEEETV Optimal power flow (OPF) is one of the most important optimization problems in the energy industry. In its simplest form, OPF attempts to find the optimal... optimal power flow graph neural networks using https://scholars.duke.edu/publication/1531165 Scholars@Duke publication: Graph neural networks for natural language processing: A survey graph neural networks natural language processing https://auto.economictimes.indiatimes.com/tag/graph+neural+networks Graph neural networks - Latest graph neural networks , Information & Updates - Auto -ET Auto ETAuto.com brings latest graph neural networks news, views and updates from all top sources for the Indian Auto industry. graph neural networks latest information updates auto https://arxiv.org/abs/2211.07823 [2211.07823] Graph Neural Networks for Causal Inference Under Network Confounding Abstract page for arXiv paper 2211.07823: Graph Neural Networks for Causal Inference Under Network Confounding graph neural networks causal inference https://pure.psu.edu/en/publications/gnncert-deterministic-certification-of-graph-neural-networks-agai/ GNNCERT: DETERMINISTIC CERTIFICATION OF GRAPH NEURAL NETWORKS AGAINST ADVERSARIAL PERTURBATIONS -... graph neural networks deterministic certification adversarial perturbations https://choiyoonhyuk.github.io/publications/c6/ Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation - AI... Mar 24, 2025 - personal description graph neural networks https://engineering.oregonstate.edu/events/challenges-and-trade-offs-graph-neural-networks Challenges and Trade-Offs for Graph Neural Networks | College of Engineering | Oregon State... Mar 19, 2025 - Since their introduction around a decade ago, graph neural networks (GNNs) have quickly become the state-of-the-art method for many graph learning tasks.... graph neural networks https://scholars.duke.edu/publication/1611526 Scholars@Duke publication: LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation graph neural networks large scale https://arxiv.org/abs/1811.00210 [1811.00210] Online Planner Selection with Graph Neural Networks and Adaptive Scheduling Abstract page for arXiv paper 1811.00210: Online Planner Selection with Graph Neural Networks and Adaptive Scheduling graph neural networks online planner https://research.ibm.com/publications/learning-physical-dynamics-with-subequivariant-graph-neural-networks Learning Physical Dynamics with Subequivariant Graph Neural Networks for NeurIPS 2022 - IBM Research Learning Physical Dynamics with Subequivariant Graph Neural Networks for NeurIPS 2022 by Jiaqi Han et al. graph neural networks https://scholars.duke.edu/publication/1616715 Scholars@Duke publication: Concept Graph Neural Networks for Surgical Video Understanding. graph neural networks surgical video scholars duke publication https://arxiv.org/abs/2307.04937 [2307.04937] Towards Fair Graph Neural Networks via Graph Counterfactual Abstract page for arXiv paper 2307.04937: Towards Fair Graph Neural Networks via Graph Counterfactual graph neural networks towards fair via https://arxiv.org/abs/2512.08344v1 [2512.08344v1] Enhancing Explainability of Graph Neural Networks Through Conceptual and Structural... Abstract page for arXiv paper 2512.08344v1: Enhancing Explainability of Graph Neural Networks Through Conceptual and Structural Analyses and Their Extensions graph neural networks https://par.nsf.gov/biblio/10611016-learning-differentiable-tensegrity-dynamics-using-graph-neural-networks Learning Differentiable Tensegrity Dynamics using Graph Neural Networks | NSF Public Access... This page contains metadata information for the record with PAR ID 10611016 graph neural networks learning differentiable tensegrity dynamics https://indico.cern.ch/event/1128328/contributions/4900744/ Mini-workshop on Graph Neural Networks for Tracking (June 3, 2022): Heterogeneous GNN for tracking... Graph networks show great promise for HEP tracking on detectors ranging from silicon trackers to LAr TPCs. As the demonstrators are applied to increasingly... graph neural networks https://www.mis.mpg.de/events/event/two-aspects-of-graph-neural-networks-and-hyperbolic-geometry Two Aspects of Graph Neural Networks and Hyperbolic Geometry in Workshop on Geometry and Machine... graph neural networks https://scholars.duke.edu/publication/1640764 Scholars@Duke publication: Concept Graph Neural Networks for Surgical Video Understanding graph neural networks surgical video scholars duke publication https://research.facebook.com/publications/hyperbolic-graph-neural-networks/ Hyperbolic Graph Neural Networks - Meta Research We develop a scalable algorithm for modeling the structural properties of graphs, comparing Euclidean and hyperbolic geometry. In our experiments, we show that... graph neural networks hyperbolic meta research https://dspace.mit.edu/handle/1721.1/154281?show=full Examining graph neural networks for crystal structures: Limitations and opportunities for capturing... graph neural networks crystal structures examining https://arxiv.org/abs/2208.04852v1 [2208.04852v1] Graph neural networks for the prediction of molecular structure-property... Abstract page for arXiv paper 2208.04852v1: Graph neural networks for the prediction of molecular structure-property relationships graph neural networks for the https://uu.diva-portal.org/smash/record.jsf?faces-redirect=true&language=no&searchType=SIMPLE&query=&af=%5B%5D&aq=%5B%5B%5D%5D&aq2=%5B%5B%5D%5D&aqe=%5B%5D&pid=diva2%3A1744983&noOfRows=50&sortOrder=author_sort_asc&sortOrder2=title_sort_asc&onlyFullText=false&sf=all Graph Neural Networks for low-energy event classification & reconstruction in IceCube graph neural networks low energy https://research.tudelft.nl/en/publications/aggregation-graph-neural-networks/ Aggregation Graph Neural Networks - TU Delft Research Portal graph neural networks tu delft aggregation research portal https://arxiv.org/abs/2210.06391v1 [2210.06391v1] What Makes Graph Neural Networks Miscalibrated? Abstract page for arXiv paper 2210.06391v1: What Makes Graph Neural Networks Miscalibrated? graph neural networks makes https://openreview.net/forum?id=dF6aEW3_62O You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs... we carry out the first-of-its-kind exploration of discovering matching untrained GNNs. https://research.ibm.com/publications/expressive-1-lipschitz-neural-networks-for-robust-multiple-graph-learning-against-adversarial-attacks Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial... Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks for ICML 2021 by Xin Zhao et al. neural networks https://github.com/tech-srl/bottleneck/ GitHub - tech-srl/bottleneck: Code for the paper: "On the Bottleneck of Graph Neural Networks and... Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications" - tech-srl/bottleneck https://ignnition.org/ IGNNITION - Fast prototyping of Graph Neural Networks Oct 30, 2024 - IGNNITION is the ideal framework for beginners in neural network programming. Run your own Graph Neural Network model in three simple steps. fast prototyping graph neural networks https://ideas.repec.org/p/amz/wpaper/2022-30.html Calibrating Agent-based Models to Microdata with Graph Neural Networks Downloadable! Calibrating agent-based models (ABMs) to data is among the most fundamental requirements to ensure the model fulfils its desired purpose. In... agent based models calibrating microdata graph neural https://www.sei.cmu.edu/library/graph-convolutional-neural-networks-3/ Graph Convolutional Neural Networks | CMU Software Engineering Institute This project used graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs). convolutional neural networks software engineering graph cmu institute https://collaborate.princeton.edu/en/publications/deeptrace-learning-to-optimize-contact-tracing-in-epidemic-networ/ DeepTrace: Learning to Optimize Contact Tracing in Epidemic Networks With Graph Neural Networks -... contact tracing https://impact.ornl.gov/en/publications/snnvis-visualizing-graph-embedding-of-evolutionary-optimization-f/ SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks - Oak... spiking neural networks https://www.sei.cmu.edu/library/graph-convolutional-neural-networks-gcnn-collection/ Graph Convolutional Neural Networks (GCNN) Collection | CMU Software Engineering Institute These publications describe the SEI's applied graph signal processing techniques that create new tools for GCNNs. convolutional neural networks software engineering graph collection cmu https://cibb2026.teralab.ai/tracks/special-networks-and-graph-neural-networks-for-bridging-bioinformatics-and-medicine/ Networks and Graph Neural Networks for Bridging Bioinformatics and Medicine The workshop aims to strengthen the dialogue between computational scientists, bioinformaticians, and clinicians by focusing on the role of network science and... networks graph neural bridging bioinformatics https://www.ipmc.cnrs.fr/fr/publication/using-graph-neural-networks-to-reconstruct-charged-pion-showers-in-the-cms-high-granularity-calorimeter/ Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity...