A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases | Paper Citation Record

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Neural Machine Translation by Jointly Learning to Align and Translate

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Relational inductive biases, deep learning, and graph networks

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: International conference on machine learning

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This paper cites IEEE Signal Processing Magazine 34(4), 18–42 (2017).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases IEEE Signal Processing Magazine 34(4), 18–42 (2017)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Spectral Networks and Locally Connected Networks on Graphs

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: International Conference on Medical Image Computing and Computer-Assisted Intervention

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases segmenta- tion and surface reconstruction

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This paper cites Neuroimage 31(3), 968–980 (2006).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Neuroimage 31(3), 968–980 (2006)

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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This paper cites IEEE Transactions on knowledge and data engineering 19(3), 355–369 (2007).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases IEEE Transactions on knowledge and data engineering 19(3), 355–369 (2007)

Reference 10

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Transfer Learning with Clinical Concept Embeddings from Large Language Models

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: International Conference on Machine Learning

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Supervised sequence labelling with recurrent neural networks pp

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This paper cites IEEE transactions on neural networks and learning systems 28(10), 2222–2232 (2016).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases IEEE transactions on neural networks and learning systems 28(10), 2222–2232 (2016)

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This paper cites GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Inductive Representation Learning on Large Graphs

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Atlas: Few-shot Learning with Retrieval Augmented Language Models

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Categorical Reparameterization with Gumbel-Softmax

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases StructGPT: A General Framework for Large Language Model to Reason over Structured Data

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Semi-Supervised Classification with Graph Convolutional Networks

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Variational Graph Auto-Encoders

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases MedRxiv pp

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This paper cites Advances in Neural Information Processing Systems 33, 9459–9474 (2020).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Advances in Neural Information Processing Systems 33, 9459–9474 (2020)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: IJCAI

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Pro- ceedings of the 30th ACM international conference on information & knowledge management

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Augmented Large Language Models with Parametric Knowledge Guiding

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Biological psychiatry 89(8), 757–765 (2021)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the IEEE/CVF International Conference on Computer Vision

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Can Large Language Models Empower Molecular Property Prediction?

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Neural computation 19(3), 757–779 (2007)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Overlapping Community Detection with Graph Neural Networks

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases NeuroImage: Clinical 30, 102620 (2021)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Medical image analysis 83, 102674 (2023)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases IEEE transactions on neural networks and learning systems (2022)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Meta-Radiology p

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Neural Networks 143, 669–677 (2021)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Neuroimage 15(1), 273–289 (2002)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Advances in neural information pro- cessing systems 30 (2017)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Graph Attention Networks

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Findings of the Association for Computational Linguistics: EMNLP 2024

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases NPJ precision oncology 6(1), 45 (2022)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the 2024 Conference on Empirical Methods in Nat- ural Language Processing

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the 26th Asia and South Pacific Design Automation Conference

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Frontiers in Aging Neuroscience 14, 959394 (2022)

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases KEY ENABLING TECHNOLOGY FOR SCIENTIFIC MACHINE LEARNING 60

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining

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A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2020 57th ACM/IEEE Design Automation Conference (DAC)

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This paper cites IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 39(11), 3445–3457 (2020).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 39(11), 3445–3457 (2020)

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.295521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a1b985c1-87f1-4bfe-ae45-fd04786f661b · outbound

This paper cites Decentralized Unsupervised Learning of Visual Representations.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Decentralized Unsupervised Learning of Visual Representations

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T19:56:15.582993Z

Source-reported events for the cited work

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Observation 09c0ffe6-5870-442f-84b4-9c380d43e4f6 · outbound

This paper cites In: 2021 58th ACM/IEEE Design Automation Conference (DAC).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2021 58th ACM/IEEE Design Automation Conference (DAC)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.282225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 52998260-5710-4047-a816-fcb7f814f386 · outbound

This paper cites In: Pro- ceedings of the AAAI Conference on Artificial Intelligence.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Pro- ceedings of the AAAI Conference on Artificial Intelligence

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.262247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1d3d043e-70a2-4689-baa9-e45fb6450503 · outbound

This paper cites In: 2021 IEEE/ACM International Conference On Computer Aided De- sign (ICCAD).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2021 IEEE/ACM International Conference On Computer Aided De- sign (ICCAD)

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.246080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ee7a0fed-16be-4d98-a71d-dfe2a3e8057b · outbound

This paper cites Medical Image Analysis 81, 102564 (2022).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Medical Image Analysis 81, 102564 (2022)

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.228923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 41616109-d011-4bd3-b6d1-e0135c1c80d8 · outbound

This paper cites In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.210207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55b78ec6-cd2b-463f-939e-1fddb6233270 · outbound

This paper cites In: 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.192657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 49f7fe95-1d9d-4147-886b-eb9a55c7616e · outbound

This paper cites Drug Discovery Today 26(6), 1382–1393 (2021).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Drug Discovery Today 26(6), 1382–1393 (2021)

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.176817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dadb71c5-998b-4a9a-bcab-2734ad062522 · outbound

This paper cites How Powerful are Graph Neural Networks?.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases How Powerful are Graph Neural Networks?

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T19:56:15.625046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb099f12-e64c-48f2-b43d-114fc4c50cf7 · outbound

This paper cites Language is All a Graph Needs.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Language is All a Graph Needs

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-11T19:56:15.629953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34e70f00-59ea-4ac3-b671-f97287c8cd25 · outbound

This paper cites Dynamic Uncertainty Ranking: Enhancing Retrieval-Augmented In-Context Learning for Long-Tail Knowledge in LLMs.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Dynamic Uncertainty Ranking: Enhancing Retrieval-Augmented In-Context Learning for Long-Tail Knowledge in LLMs

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T19:56:15.634258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3819d785-d599-4fbd-8946-fdbca34fae03 · outbound

This paper cites Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T19:56:15.639992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a6fbd5c-2edc-42ac-b299-a8b9473e364e · outbound

This paper cites In: Findings of the Association for Computational Linguistics: NAACL 2024.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: Findings of the Association for Computational Linguistics: NAACL 2024

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.154664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 76a4d5ac-a4b3-4487-9f3b-831259cf3b6d · outbound

This paper cites In: 2022 IEEE International Conference on Data Mining (ICDM).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2022 IEEE International Conference on Data Mining (ICDM)

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.139500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e4126fb0-7763-4fe0-bb4b-02a128ae1231 · outbound

This paper cites In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI)

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.124224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 624405f6-4c25-4455-85d0-d4e4d99f61ac · outbound

This paper cites In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI).

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI)

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:56:16.108585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 09204a07-0d0a-4267-a756-472f776b0ad6 · outbound

This paper cites A Survey of Large Language Models.

A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases A Survey of Large Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T19:56:15.660301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers