:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Kodama, Nathan X., Loparo, Kenneth A.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2508.16776
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Diffusion-Guided Renormalization of Neural Systems via Tensor Networks
by: Kodama, Nathan X.
Published: (2025)

Thermodynamic Performance Limits for Score-Based Diffusion Models
by: Kodama, Nathan X., et al.
Published: (2025)

Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion Models
by: Evdaimon, Iakovos, et al.
Published: (2024)

A Generative Graph Contrastive Learning Model with Global Signal
by: Wei, Xiaofan, et al.
Published: (2025)

Hyperbolic Geometric Latent Diffusion Model for Graph Generation
by: Fu, Xingcheng, et al.
Published: (2024)

Graph Signal Generative Diffusion Models
by: Uslu, Yigit Berkay, et al.
Published: (2025)

AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields
by: Serrano, Louis, et al.
Published: (2024)

Deep Latent Variable Modeling of Physiological Signals
by: Vo, Khuong
Published: (2024)

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization
by: Nguyen, Van Khoa, et al.
Published: (2024)

Contrastive Learning Boosts Deterministic and Generative Models for Weather Data
by: Bailey, Nathan
Published: (2026)

Multi-Objective Latent Space Optimization of Generative Molecular Design Models
by: Abeer, A N M Nafiz, et al.
Published: (2022)

A Deep Latent Space Model for Graph Representation Learning
by: Yang, Hanxuan, et al.
Published: (2021)

Graph Neural Networks as Ordering Heuristics for Parallel Graph Coloring
by: Langedal, Kenneth, et al.
Published: (2024)

Graph Neural Networks for Community Detection in Graph Signal Analysis
by: Cavoretto, Roberto, et al.
Published: (2026)

Rank Is Not Capacity: Spectral Occupancy for Latent Graph Models
by: Nakis, Nikolaos, et al.
Published: (2026)

Learning High-Quality Latent Representations for Anomaly Detection and Signal Integrity Enhancement in High-Speed Signals
by: Usama, Muhammad, et al.
Published: (2025)

A Note on Graphon-Signal Analysis of Graph Neural Networks
by: Rauchwerger, Levi, et al.
Published: (2025)

Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
by: Fuchsgruber, Dominik, et al.
Published: (2024)

Learning Latent Graph Structures and their Uncertainty
by: Manenti, Alessandro, et al.
Published: (2024)

Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
by: Zhou, Cai, et al.
Published: (2024)

JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation
by: Shi, Ji, et al.
Published: (2025)

Learning Time-Varying Graphs from Incomplete Graph Signals
by: Peng, Chuansen, et al.
Published: (2025)

Navigating the Latent Space Dynamics of Neural Models
by: Fumero, Marco, et al.
Published: (2025)

Learning Interpretable Features in Audio Latent Spaces via Sparse Autoencoders
by: Paek, Nathan, et al.
Published: (2025)

Generative Modeling of Neural Dynamics via Latent Stochastic Differential Equations
by: ElGazzar, Ahmed, et al.
Published: (2024)

Refining Latent Representations: A Generative SSL Approach for Heterogeneous Graph Learning
by: Hu, Yulan, et al.
Published: (2023)

A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs
by: Yang, Sikun, et al.
Published: (2023)

Graph-Aware Diffusion for Signal Generation
by: Rozada, Sergio, et al.
Published: (2025)

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation
by: Zhuang, Yuanxin, et al.
Published: (2025)

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

Hierarchical Stochastic Differential Equation Models for Latent Manifold Learning in Neural Time Series
by: Rajaei, Pedram, et al.
Published: (2025)

Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings
by: Sengar, Aditya, et al.
Published: (2025)

Graph Filters for Signal Processing and Machine Learning on Graphs
by: Isufi, Elvin, et al.
Published: (2022)

Latent Schr{ö}dinger Bridge Diffusion Model for Generative Learning
by: Jiao, Yuling, et al.
Published: (2024)

Bootstrap Latents of Nodes and Neighbors for Graph Self-Supervised Learning
by: Liu, Yunhui, et al.
Published: (2024)

Federated Latent Factor Learning for Recovering Wireless Sensor Networks Signal with Privacy-Preserving
by: Yu, Chengjun, et al.
Published: (2025)

Unified Generative Latent Representation for Functional Brain Graphs
by: Abulikemu, Subati, et al.
Published: (2025)

A Multi-Graph Convolutional Neural Network Model for Short-Term Prediction of Turning Movements at Signalized Intersections
by: Palit, Jewel Rana, et al.
Published: (2024)

Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction
by: Castro-Correa, Jhon A., et al.
Published: (2024)

Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks
by: Rusch, T. Konstantin, et al.
Published: (2024)