Cover Image

Nonstationary Sparse Spectral Permanental Process

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Zicheng, Zhang, Yixuan, Ling, Zenan, Fan, Xuhui, Zhou, Feng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Causal Temporal Representation Learning with Nonstationary Sparse Transition
by: Song, Xiangchen, et al.
Published: (2024)

Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures
by: Ling, Zenan, et al.
Published: (2024)

Forecasting Sparse Movement Speed of Urban Road Networks with Nonstationary Temporal Matrix Factorization
by: Chen, Xinyu, et al.
Published: (2022)

Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
by: Ke, Tianjun, et al.
Published: (2023)

Navigating Towards Fairness with Data Selection
by: Zhang, Yixuan, et al.
Published: (2024)

Score Matching for Estimating Finite Point Processes
by: Cao, Haoqun, et al.
Published: (2025)

Regular Fourier Features for Nonstationary Gaussian Processes
by: Jawaid, Arsalan, et al.
Published: (2026)

Causal Inference from Slowly Varying Nonstationary Processes
by: Du, Kang, et al.
Published: (2024)

SEEK: Self-adaptive Explainable Kernel For Nonstationary Gaussian Processes
by: Negarandeh, Nima, et al.
Published: (2025)

Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression
by: Lyu, Junliang, et al.
Published: (2024)

TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes
by: Meng, Zizhuo, et al.
Published: (2024)

Predicting Covariate-Driven Spatial Deformation for Nonstationary Gaussian Processes
by: Gu, Minghao, et al.
Published: (2026)

Series-to-Series Diffusion Bridge Model
by: Yang, Hao, et al.
Published: (2024)

Marked Temporal Bayesian Flow Point Processes
by: Chen, Hui, et al.
Published: (2024)

Nonstationary Reinforcement Learning with Linear Function Approximation
by: Zhou, Huozhi, et al.
Published: (2020)

Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
by: Nadew, Yididiya Y., et al.
Published: (2024)

A Framework for Nonstationary Gaussian Processes with Neural Network Parameters
by: James, Zachary, et al.
Published: (2025)

Bias Mitigation in Fine-tuning Pre-trained Models for Enhanced Fairness and Efficiency
by: Zhang, Yixuan, et al.
Published: (2024)

Reinforcement Learning for Pollution Detection in a Randomized, Sparse and Nonstationary Environment with an Autonomous Underwater Vehicle
by: Zieglmeier, Sebastian, et al.
Published: (2025)

Coverage and Bias of Street View Imagery in Mapping the Urban Environment
by: Fan, Zicheng, et al.
Published: (2024)

Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approaches
by: Zhou, Feng, et al.
Published: (2025)

Describing Nonstationary Data Streams in Frequency Domain
by: Komorniczak, Joanna
Published: (2025)

Nonstationary Time Series Forecasting via Unknown Distribution Adaptation
by: Li, Zijian, et al.
Published: (2024)

Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations
by: Zhou, Shaoqian, et al.
Published: (2025)

Accurate Remaining Useful Life Prediction with Uncertainty Quantification: a Deep Learning and Nonstationary Gaussian Process Approach
by: Xu, Zhaoyi, et al.
Published: (2021)

Federated Neural Nonparametric Point Processes
by: Chen, Hui, et al.
Published: (2024)

Adaptive Linear Embedding for Nonstationary High-Dimensional Optimization
by: Wen, Yuejiang, et al.
Published: (2025)

A State-Space Approach to Nonstationary Discriminant Analysis
by: Xie, Shuilian, et al.
Published: (2025)

Online Conformal Model Selection for Nonstationary Time Series
by: Li, Shibo, et al.
Published: (2025)

Diving into Kronecker Adapters: Component Design Matters
by: Bai, Jiayu, et al.
Published: (2026)

Learning When to Restart: Nonstationary Newsvendor from Uncensored to Censored Demand
by: Chen, Xin, et al.
Published: (2025)

Adaptive Discretization for Consistency Models
by: Bai, Jiayu, et al.
Published: (2025)

Byte-token Enhanced Language Models for Temporal Point Processes Analysis
by: Kong, Quyu, et al.
Published: (2025)

A Survey on Pre-Trained Diffusion Model Distillations
by: Fan, Xuhui, et al.
Published: (2025)

IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks
by: Lin, Junchao, et al.
Published: (2024)

Learning to Query History: Nonstationary Classification via Learned Retrieval
by: Gammell, Jimmy, et al.
Published: (2026)

Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent
by: Lee, Joongkyu, et al.
Published: (2026)

Fast Rates for Nonstationary Weighted Risk Minimization
by: Brock, Tobias, et al.
Published: (2026)

Uncertainty-Aware Decision Transformer for Stochastic Driving Environments
by: Li, Zenan, et al.
Published: (2023)

Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
by: Zhao, Jialin, et al.
Published: (2024)