Image de couverture de livre

Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Liu, Song, Wang, Leyang, Wang, Yakun
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
par: Williams, Daniel J., et autres
Publié: (2024)

Zero-Flow Encoders
par: Wang, Yakun, et autres
Publié: (2026)

Exponential Family Attention
par: Wibisono, Kevin Christian, et autres
Publié: (2025)

Linear Independence of Generalized Neurons and Related Functions
par: Zhang, Leyang
Publié: (2024)

Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits
par: Liu, Shuai, et autres
Publié: (2024)

Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs
par: Adachi, Masaki, et autres
Publié: (2026)

Diffusion Models for Inverse Problems in the Exponential Family
par: Micheli, Alessandro, et autres
Publié: (2025)

Inversion-Free Natural Gradient Descent on Riemannian Manifolds
par: Draca, Dario, et autres
Publié: (2026)

Dropout Regularization in Extended Generalized Linear Models based on Double Exponential Families
par: Schwienhorst, Benedikt Lütke, et autres
Publié: (2023)

Joint Representation Learning and Clustering via Gradient-Based Manifold Optimization
par: Liu, Sida, et autres
Publié: (2026)

Exponential Family Discriminant Analysis: Generalizing LDA-Style Generative Classification to Non-Gaussian Models
par: Lakkapragada, Anish
Publié: (2026)

Direct Fisher Score Estimation for Likelihood Maximization
par: Khoo, Sherman, et autres
Publié: (2025)

Exponential Family Variational Flow Matching for Tabular Data Generation
par: Guzmán-Cordero, Andrés, et autres
Publié: (2025)

Missing Data Imputation by Reducing Mutual Information with Rectified Flows
par: Yu, Jiahao, et autres
Publié: (2025)

Counterfactual Generative Models for Time-Varying Treatments
par: Wu, Shenghao, et autres
Publié: (2023)

Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks
par: Nguyen, Duong Thuy Anh, et autres
Publié: (2024)

Knowledge-Guided Time-Varying Causal Inference for Arctic Sea Ice Dynamics
par: Sampath, Akila, et autres
Publié: (2026)

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds
par: Li, Liuzhuozheng, et autres
Publié: (2026)

Varying Manifolds in Diffusion: From Time-varying Geometries to Visual Saliency
par: Chen, Junhao, et autres
Publié: (2024)

Universal and Transferable Adversarial Attack on Large Language Models Using Exponentiated Gradient Descent
par: Biswas, Sajib, et autres
Publié: (2025)

Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families
par: Hulsman, Roel, et autres
Publié: (2026)

Convergence of Natural Policy Gradient for a Family of Infinite-State Queueing MDPs
par: Grosof, Isaac, et autres
Publié: (2024)

Large Language Models are Few-shot Multivariate Time Series Classifiers
par: Chen, Yakun, et autres
Publié: (2025)

Stein's Lemma for the Reparameterization Trick with Exponential Family Mixtures
par: Lin, Wu, et autres
Publié: (2019)

Curvature Tuning: Provable Training-free Model Steering From a Single Parameter
par: Hu, Leyang, et autres
Publié: (2025)

Gradient-Guided Annealing for Domain Generalization
par: Ballas, Aristotelis, et autres
Publié: (2025)

Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal
par: Wang, Junlin
Publié: (2026)

Generative Model Inversion Through the Lens of the Manifold Hypothesis
par: Peng, Xiong, et autres
Publié: (2025)

Structure-Dependent Regret and Constraint Violation Bounds for Online Convex Optimization with Time-Varying Constraints
par: Liu, Xiufeng, et autres
Publié: (2026)

Manifold-Guided Attention Steering
par: Li, Ian, et autres
Publié: (2026)

A Unified Theory of Exact Inference and Learning in Exponential Family Latent Variable Models
par: Sokoloski, Sacha
Publié: (2024)

Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
par: Chen, Jun, et autres
Publié: (2023)

Revisiting Projection-Free Online Learning with Time-Varying Constraints
par: Wang, Yibo, et autres
Publié: (2025)

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
par: Biswas, Sajib, et autres
Publié: (2025)

Graph Laplacian Learning with Exponential Family Noise
par: Shi, Changhao, et autres
Publié: (2023)

Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers
par: Blasingame, Zander W., et autres
Publié: (2025)

Geodesic Gradient Descent: A Generic and Learning-rate-free Optimizer on Objective Function-induced Manifolds
par: Hu, Liwei, et autres
Publié: (2026)

T2S-MPC: Time-Embedded Online Adaptive Model Predictive Control for Time-Varying Dynamics
par: Shen, Zeyu, et autres
Publié: (2026)

VarDiU: A Variational Diffusive Upper Bound for One-Step Diffusion Distillation
par: Wang, Leyang, et autres
Publié: (2025)

Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection
par: Cichocki, Andrzej, et autres
Publié: (2024)