Imagen de Portada

Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Weihan, Wang, Yule, Li, Chengrui, Wu, Anqi
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
por: Li, Weihan, et al.
Publicado: (2024)

Forward $χ^2$ Divergence Based Variational Importance Sampling
por: Li, Chengrui, et al.
Publicado: (2023)

A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
por: Li, Chengrui, et al.
Publicado: (2024)

Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
por: Wang, Yule, et al.
Publicado: (2024)

Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion
por: Wang, Yule, et al.
Publicado: (2025)

A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement
por: Li, Chengrui, et al.
Publicado: (2025)

A Disentangled Low-Rank RNN Framework for Uncovering Neural Connectivity and Dynamics
por: Li, Chengrui, et al.
Publicado: (2025)

Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models
por: Wang, Yule, et al.
Publicado: (2023)

Learning When to Look: On-Demand Keypoint-Video Fusion for Animal Behavior Analysis
por: Li, Weihan, et al.
Publicado: (2026)

Time-Varying Gaussian Process Bandits with Unknown Prior
por: Ziomek, Juliusz, et al.
Publicado: (2024)

No-Regret Gaussian Process Optimization of Time-Varying Functions
por: Mauduit, Eliabelle, et al.
Publicado: (2025)

Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
por: Li, Jialin, et al.
Publicado: (2024)

Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference
por: Jiang, Xiaoyu, et al.
Publicado: (2024)

Efficient Graph Condensation via Gaussian Process
por: Wang, Lin, et al.
Publicado: (2025)

ReDiSC: A Reparameterized Masked Diffusion Model for Scalable Node Classification with Structured Predictions
por: Li, Yule, et al.
Publicado: (2025)

Theory and Algorithms for Learning with Multi-Class Abstention and Multi-Expert Deferral
por: Mao, Anqi
Publicado: (2025)

Bayesian Modeling and Estimation of Linear Time-Varying Systems using Neural Networks and Gaussian Processes
por: Shulman, Yaniv
Publicado: (2025)

Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
por: Wei, Yunyue, et al.
Publicado: (2024)

Scalable Varied-Density Clustering via Graph Propagation
por: Pham, Ninh, et al.
Publicado: (2025)

Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains
por: Liu, Haitao, et al.
Publicado: (2022)

Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning
por: Chang, Chun-Yi, et al.
Publicado: (2025)

Scalable Gaussian Processes with Latent Kronecker Structure
por: Lin, Jihao Andreas, et al.
Publicado: (2025)

Scalable Deep Basis Kernel Gaussian Processes
por: Zhu, Yunqin, et al.
Publicado: (2025)

Graph Random Features for Scalable Gaussian Processes
por: Zhang, Matthew, et al.
Publicado: (2025)

Pareto Set Learning for Multi-Objective Reinforcement Learning
por: Liu, Erlong, et al.
Publicado: (2025)

Calibrating Transformers via Sparse Gaussian Processes
por: Chen, Wenlong, et al.
Publicado: (2023)

Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning
por: Li, Xinran, et al.
Publicado: (2025)

BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
por: Hung, Yu-Heng, et al.
Publicado: (2025)

A hitchhiker's guide to Poisson gradient estimation
por: Ibrahim, Michael, et al.
Publicado: (2026)

Learning High-Order Relationships of Brain Regions
por: Qiu, Weikang, et al.
Publicado: (2023)

Learning Time-Varying Graph Signals via Koopman
por: Krishnan, Sivaram, et al.
Publicado: (2025)

Robust Offline Reinforcement Learning for Non-Markovian Decision Processes
por: Huang, Ruiquan, et al.
Publicado: (2024)

Regularized Multi-output Gaussian Convolution Process with Domain Adaptation
por: Xinming, Wang, et al.
Publicado: (2024)

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
por: Shao, Junli, et al.
Publicado: (2025)

Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference
por: Ketenci, Mert, et al.
Publicado: (2023)

Scalable Gaussian Processes: Advances in Iterative Methods and Pathwise Conditioning
por: Lin, Jihao Andreas
Publicado: (2025)

Revisiting Projection-Free Online Learning with Time-Varying Constraints
por: Wang, Yibo, et al.
Publicado: (2025)

Safe Active Learning for Time-Series Modeling with Gaussian Processes
por: Zimmer, Christoph, et al.
Publicado: (2024)

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process
por: Saito, Issei, et al.
Publicado: (2025)

Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks
por: Antoran, Javier
Publicado: (2024)