:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Lei, Chen, Zhiqian, Lu, Chang-Tien, Zhao, Liang
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2405.16409
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs
by: Granmo, Ole-Christoffer, et al.
Published: (2025)

Enhancing Explainability of Graph Neural Networks Through Conceptual and Structural Analyses and Their Extensions
by: Bui, Tien Cuong
Published: (2025)

TADPO: Reinforcement Learning Goes Off-road
by: Wu, Zhouchonghao, et al.
Published: (2026)

Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models -- The Story Goes On
by: Zeng, Liang, et al.
Published: (2024)

Universal Prompt Tuning for Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2022)

Non-Euclidean Spatial Graph Neural Network
by: Zhang, Zheng, et al.
Published: (2023)

Conformalized Link Prediction on Graph Neural Networks
by: Zhao, Tianyi, et al.
Published: (2024)

A Unified Kernel for Neural Network Learning
by: Zhang, Shao-Qun, et al.
Published: (2024)

GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)

Whither Bias Goes, I Will Go: An Integrative, Systematic Review of Algorithmic Bias Mitigation
by: Hickman, Louis, et al.
Published: (2024)

WATS: Calibrating Graph Neural Networks with Wavelet-Aware Temperature Scaling
by: Li, Xiaoyang, et al.
Published: (2025)

LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
by: Du, Lin, et al.
Published: (2025)

Combinatorial Optimization with Automated Graph Neural Networks
by: Liu, Yang, et al.
Published: (2024)

A Little Human Data Goes A Long Way
by: Ashok, Dhananjay, et al.
Published: (2024)

Towards Reliable Evaluation of Adversarial Robustness for Spiking Neural Networks
by: Wang, Jihang, et al.
Published: (2025)

Decision-focused Graph Neural Networks for Combinatorial Optimization
by: Liu, Yang, et al.
Published: (2024)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)

Heterophilic Graph Neural Networks Optimization with Causal Message-passing
by: Wang, Botao, et al.
Published: (2024)

PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation
by: Chang, Ching, et al.
Published: (2025)

Deep Sensitivity Analysis for Objective-Oriented Combinatorial Optimization
by: Gireesan, Ganga, et al.
Published: (2024)

SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training
by: Gu, Xizhi, et al.
Published: (2024)

Prediction Is All MoE Needs: Expert Load Distribution Goes from Fluctuating to Stabilizing
by: Cong, Peizhuang, et al.
Published: (2024)

Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks
by: Wang, Zhili, et al.
Published: (2023)

GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs
by: Zhao, Songwei, et al.
Published: (2025)

OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
by: Li, Haoyang, et al.
Published: (2025)

Towards Interpreting Multi-Objective Feature Associations
by: Pillai, Nisha, et al.
Published: (2024)

Line Goes Up? Inherent Limitations of Benchmarks for Evaluating Large Language Models
by: Fodor, James
Published: (2025)

Improving MLLM Training Efficiency via Stage-Aware Sparsity
by: Shi, Kean, et al.
Published: (2025)

Generative AI Meets Future Cities: Towards an Era of Autonomous Urban Intelligence
by: Wang, Dongjie, et al.
Published: (2023)

Missing-Modality-Aware Graph Neural Network for Cancer Classification
by: Tabakhi, Sina, et al.
Published: (2025)

Symmetry in Neural Network Parameter Spaces
by: Zhao, Bo, et al.
Published: (2025)

KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2025)

DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks
by: Zhang, Zeyu, et al.
Published: (2024)

Scalable Neural Network Kernels
by: Sehanobish, Arijit, et al.
Published: (2023)

Towards Initialization-dependent and Non-vacuous Generalization Bounds for Overparameterized Shallow Neural Networks
by: Lei, Yunwen, et al.
Published: (2026)

"I've Seen How This Goes": Characterizing Diversity via Progressive Conditional Surprise
by: Khoriaty, Matthew, et al.
Published: (2026)

Anomaly Detection Based on Critical Paths for Deep Neural Networks
by: Zhao, Fangzhen, et al.
Published: (2025)

Faithful Interpretation for Graph Neural Networks
by: Hu, Lijie, et al.
Published: (2024)

Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025)

Attention Consistency Regularization for Interpretable Early-Exit Neural Networks
by: Zhao, Yanhua
Published: (2026)