:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dimasaka, Joshua, Geiß, Christian, So, Emily
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2508.01310
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Global Mapping of Exposure and Physical Vulnerability Dynamics in Least Developed Countries using Remote Sensing and Machine Learning
by: Dimasaka, Joshua, et al.
Published: (2024)

DeepC4: Deep Conditional Census-Constrained Clustering for Large-scale Multitask Spatial Disaggregation of Urban Morphology
by: Dimasaka, Joshua, et al.
Published: (2025)

Graph State-Space Models and Latent Relational Inference
by: Zambon, Daniele, et al.
Published: (2023)

Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
by: Papež, Milan, et al.
Published: (2025)

A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification
by: Yap, Sin-Yee, et al.
Published: (2023)

Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
by: Wang, Qingyi, et al.
Published: (2023)

DisasterLex: An Expert Concept-to-Schema Knowledge Graph for Geospatial Reasoning in Disaster Analytics
by: Xiao, Yiming, et al.
Published: (2026)

LEO: Graph Attention Network based Hybrid Multi Sensor Extended Object Fusion and Tracking for Autonomous Driving Applications
by: Mayank, Mayank, et al.
Published: (2026)

Variational Mode-Driven Graph Convolutional Network for Spatiotemporal Traffic Forecasting
by: Ahmad, Osama, et al.
Published: (2024)

Graph Mamba: Towards Learning on Graphs with State Space Models
by: Behrouz, Ali, et al.
Published: (2024)

DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
by: Li, Dongyuan, et al.
Published: (2024)

Learning Noise-Resilient and Transferable Graph-Text Alignment via Dynamic Quality Assessment
by: Liu, Yuhang, et al.
Published: (2025)

Addressing Class Imbalance with Probabilistic Graphical Models and Variational Inference
by: Lou, Yujia, et al.
Published: (2025)

Multi-resolution Score-Based Variational Graphical Diffusion for Causal Disaster System Modeling and Inference
by: Li, Xuechun, et al.
Published: (2025)

Structured Optimal Variational Inference for Dynamic Latent Space Models
by: Zhao, Peng, et al.
Published: (2022)

HealthMamba: An Uncertainty-aware Spatiotemporal Graph State Space Model for Effective and Reliable Healthcare Facility Visit Prediction
by: Yu, Dahai, et al.
Published: (2026)

Adaptive Spatiotemporal Augmentation for Improving Dynamic Graph Learning
by: Chu, Xu, et al.
Published: (2025)

Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
by: Mi, Yuan, et al.
Published: (2024)

GG-SSMs: Graph-Generating State Space Models
by: Zubić, Nikola, et al.
Published: (2024)

ProDAG: Projected Variational Inference for Directed Acyclic Graphs
by: Thompson, Ryan, et al.
Published: (2024)

Permutation-based Inference for Variational Learning of Directed Acyclic Graphs
by: Bonilla, Edwin V., et al.
Published: (2024)

State Space Models over Directed Graphs
by: She, Junzhi, et al.
Published: (2025)

Probabilistic Programming with Programmable Variational Inference
by: Becker, McCoy R., et al.
Published: (2024)

Transformer with Koopman-Enhanced Graph Convolutional Network for Spatiotemporal Dynamics Forecasting
by: Wang, Zekai, et al.
Published: (2025)

DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models
by: Yuan, Haonan, et al.
Published: (2024)

Probabilistic Emissivity Retrieval from Hyperspectral Data via Physics-Guided Variational Inference
by: Tempelman, Joshua R., et al.
Published: (2025)

Performance Evaluation of Deep Learning-Based State Estimation: A Comparative Study of KalmanNet
by: Mehrfard, Arian, et al.
Published: (2024)

Exploring Graph Mamba: A Comprehensive Survey on State-Space Models for Graph Learning
by: Atitallah, Safa Ben, et al.
Published: (2024)

Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
by: Wang, Chloe, et al.
Published: (2024)

Variational Flow Matching for Graph Generation
by: Eijkelboom, Floor, et al.
Published: (2024)

Time Series Clustering with General State Space Models via Stochastic Variational Inference
by: Ishizuka, Ryoichi, et al.
Published: (2024)

Resilience in Knowledge Graph Embeddings
by: Sharma, Arnab, et al.
Published: (2024)

GraphPPD: Posterior Predictive Modelling for Graph-Level Inference
by: Pal, Soumyasundar, et al.
Published: (2025)

Graph Synthetic Out-of-Distribution Exposure with Large Language Models
by: Xu, Haoyan, et al.
Published: (2025)

A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation
by: Hosseini, Ryien, et al.
Published: (2024)

Space-aware Socioeconomic Indicator Inference with Heterogeneous Graphs
by: Zou, Xingchen, et al.
Published: (2024)

GrassNet: State Space Model Meets Graph Neural Network
by: Zhao, Gongpei, et al.
Published: (2024)

HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model
by: Pan, Zhenyu, et al.
Published: (2024)

Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation
by: Jing, Baoyu, et al.
Published: (2024)

Composing Non-Conjugate Factor Graphs with Closed-Form Variational Inference
by: Lukashchuk, Mykola, et al.
Published: (2026)