:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Tian, Mulin, Srivastava, Ajitesh
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2512.00421
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DTW+S: Shape-based Comparison of Time-series with Ordered Local Trend
by: Srivastava, Ajitesh
Published: (2023)

SWAT-NN: Simultaneous Weights and Architecture Training for Neural Networks in a Latent Space
by: Huang, Zitong, et al.
Published: (2025)

Simultaneous Weight and Architecture Optimization for Neural Networks
by: Huang, Zitong, et al.
Published: (2024)

Peer Disambiguation in Self-Reported Surveys using Graph Attention Networks
by: Srivastava, Ajitesh, et al.
Published: (2025)

Sparse Interpretable Deep Learning with LIES Networks for Symbolic Regression
by: Montazerin, Mansooreh, et al.
Published: (2025)

Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks
by: Aawar, Majd Al, et al.
Published: (2024)

Acoustic-to-articulatory inversion for dysarthric speech: Are pre-trained self-supervised representations favorable?
by: Maharana, Sarthak Kumar, et al.
Published: (2023)

Towards Knowledge Guided Pretraining Approaches for Multimodal Foundation Models: Applications in Remote Sensing
by: Ravirathinam, Praveen, et al.
Published: (2024)

Towards Learnable Anchor for Deep Multi-View Clustering
by: Wang, Bocheng, et al.
Published: (2025)

Towards Robust Uncertainty-Aware Incomplete Multi-View Classification
by: Chen, Mulin, et al.
Published: (2024)

Understanding Expressivity of GNN in Rule Learning
by: Qiu, Haiquan, et al.
Published: (2023)

Deep Contrastive Graph Learning with Clustering-Oriented Guidance
by: Chen, Mulin, et al.
Published: (2024)

Overcoming Non-Submodularity: Towards Constant Approximation for Network Immunization
by: Srivastava, Ajitesh, et al.
Published: (2024)

Not All Neighbors Matter: Understanding the Impact of Graph Sparsification on GNN Pipelines
by: Song, Yuhang, et al.
Published: (2026)

Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks
by: Hariri, Ali, et al.
Published: (2025)

ADMP-GNN: Adaptive Depth Message Passing GNN
by: Abbahaddou, Yassine, et al.
Published: (2025)

Toward an Operational GNN-Based Multimesh Surrogate for Fast Flood Forecasting
by: Mercier, Valentin, et al.
Published: (2026)

Belief Dynamics for Detecting Behavioral Shifts in Safe Collaborative Manipulation
by: Naik, Devashri, et al.
Published: (2026)

SmoothGNN: Smoothing-aware GNN for Unsupervised Node Anomaly Detection
by: Dong, Xiangyu, et al.
Published: (2024)

$P^2$GNN: Two Prototype Sets to boost GNN Performance
by: Jain, Arihant, et al.
Published: (2026)

Modeling Human Beliefs about AI Behavior for Scalable Oversight
by: Lang, Leon, et al.
Published: (2025)

Clustering-Oriented Generative Attribute Graph Imputation
by: Chen, Mulin, et al.
Published: (2025)

Multi-Task Curriculum Graph Contrastive Learning with Clustering Entropy Guidance
by: Zeng, Chusheng, et al.
Published: (2024)

SL-BiLEM: Structured Learnable Behavior-in-the-Loop Epidemic Modeling for Forecasting and Policy Evaluation
by: Wang, Haochun, et al.
Published: (2026)

Behavioral Inference at Scale: The Fundamental Asymmetry Between Motivations and Belief Systems
by: Starace, Jason, et al.
Published: (2025)

Improving Epidemic Analyses with Privacy-Preserving Integration of Sensitive Data
by: Guan, Zihan, et al.
Published: (2025)

On The Expressive Power of GNN Derivatives
by: Eitan, Yam, et al.
Published: (2025)

On GNN explanability with activation rules
by: Veyrin-Forrer, Luca, et al.
Published: (2024)

Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
by: Zhang, Yuxiang, et al.
Published: (2024)

MDAS-GNN: Multi-Dimensional Spatiotemporal GNN with Spatial Diffusion for Urban Traffic Risk Forecasting
by: Gao, Ziyuan
Published: (2025)

DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training
by: Liu, Renjie, et al.
Published: (2024)

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
by: Jiang, Haitian, et al.
Published: (2023)

Submodular Maximization under Supermodular Constraint: Greedy Guarantees
by: Srivastava, Ajitesh, et al.
Published: (2026)

GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation
by: Sun, Yundong, et al.
Published: (2024)

Subsampling Graphs with GNN Performance Guarantees
by: Jain, Mika Sarkin, et al.
Published: (2025)

Explaining GNN Explanations with Edge Gradients
by: He, Jesse, et al.
Published: (2025)

GNN-based Unified Deep Learning
by: Pala, Furkan, et al.
Published: (2025)

Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Individual Behavioral Learning
by: Rakhshandehroo, Radman, et al.
Published: (2025)

Breaking Symmetry Bottlenecks in GNN Readouts
by: Talhi, Mouad, et al.
Published: (2026)

SCL-GNN: Towards Generalizable Graph Neural Networks via Spurious Correlation Learning
by: Zhang, Yuxiang, et al.
Published: (2026)