Cover Image

Applications of Random Matrix Theory in Machine Learning and Brain Mapping

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Lawrence, Katrina
Format:	Preprint
Published:	2025
Subjects:	Neurons and Cognition Machine Learning Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spiking Neural Models for Decision-Making Tasks with Learning
by: Jaffard, Sophie, et al.
Published: (2025)

STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC
by: Wang, Jiyao, et al.
Published: (2024)

A Data-Driven Method to Map the Functional Organisation of Human Brain White Matter
by: Sun, Yifei, et al.
Published: (2026)

Functional Brain Network Identification in Opioid Use Disorder Using Machine Learning Analysis of Resting-State fMRI BOLD Signals
by: Temtam, Ahmed, et al.
Published: (2024)

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

ASD Classification on Dynamic Brain Connectome using Temporal Random Walk with Transformer-based Dynamic Network Embedding
by: Piriyasatit, Suchanuch, et al.
Published: (2025)

Latent Representation Learning for Multimodal Brain Activity Translation
by: Afrasiyabi, Arman, et al.
Published: (2024)

Discovering Dynamic Effective Connectome of Brain with Bayesian Dynamic DAG Learning
by: Bagheri, Abdolmahdi, et al.
Published: (2023)

DCHO: A Decomposition-Composition Framework for Predicting Higher-Order Brain Connectivity to Enhance Diverse Downstream Applications
by: Li, Weibin, et al.
Published: (2025)

BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
by: Xu, Jiaxing, et al.
Published: (2025)

HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks
by: Sadeghian, Sadaf, et al.
Published: (2024)

Analyzing Brain Activity During Learning Tasks with EEG and Machine Learning
by: Cho, Ryan, et al.
Published: (2024)

Learning Glioblastoma Tumor Heterogeneity Using Brain Inspired Topological Neural Networks
by: Paul, Ankita, et al.
Published: (2026)

NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
by: Said, Anwar, et al.
Published: (2023)

Active inference and artificial reasoning
by: Friston, Karl, et al.
Published: (2025)

Cross-Species Transfer Learning for Electrophysiology-to-Transcriptomics Mapping in Cortical GABAergic Interneurons
by: Schwider, Theo, et al.
Published: (2026)

Joint-Embedding Masked Autoencoder for Self-supervised Learning of Dynamic Functional Connectivity from the Human Brain
by: Choi, Jungwon, et al.
Published: (2024)

The Human Brain as a Combinatorial Complex
by: Sánchez, Valentina, et al.
Published: (2025)

Brain-MGF: Multimodal Graph Fusion Network for EEG-fMRI Brain Connectivity Analysis Under Psilocybin
by: Yap, Sin-Yee, et al.
Published: (2025)

Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention
by: Kamat, Anil, et al.
Published: (2025)

Adaptive Segmentation of EEG for Machine Learning Applications
by: Zhou, Johnson, et al.
Published: (2025)

Neuroprobe: Evaluating Intracranial Brain Responses to Naturalistic Stimuli
by: Zahorodnii, Andrii, et al.
Published: (2025)

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

Differentiable Optimization of Similarity Scores Between Models and Brains
by: Cloos, Nathan, et al.
Published: (2024)

Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents
by: Han, Shuo, et al.
Published: (2025)

Comparing and Scaling fMRI Features for Brain-Behavior Prediction
by: Sieler, Mikkel Schöttner, et al.
Published: (2025)

Topological Cycle Graph Attention Network for Brain Functional Connectivity
by: Huang, Jinghan, et al.
Published: (2024)

Unveiling the Heart-Brain Connection: An Analysis of ECG in Cognitive Performance
by: Sasi, Akshay, et al.
Published: (2026)

Hierarchical Multiscale Structure-Function Coupling for Brain Connectome Integration
by: Chen, Jianwei, et al.
Published: (2026)

Backward Stochastic Differential Equations-guided Generative Model for Structural-to-functional Neuroimage Translator
by: Chen, Zengjing, et al.
Published: (2025)

Efficient, simulation-free estimators of firing rates with Markovian surrogates
by: Wang, Zhongyi, et al.
Published: (2025)

Retrieving the structure of probabilistic sequences from EEG data during the goalkeeper game
by: Cabral-Passos, P. R., et al.
Published: (2025)

A Quasi-Stationary Approach to Metastability in a System of Spiking Neurons with Synaptic Plasticity
by: Pouzat, Christophe, et al.
Published: (2024)

Nonlinear Dynamical Modeling of Human Intracranial Brain Activity with Flexible Inference
by: Vaziri, Kiarash, et al.
Published: (2025)

A Foundational Brain Dynamics Model via Stochastic Optimal Control
by: Park, Joonhyeong, et al.
Published: (2025)

Brain-language fusion enables interactive neural readout and in-silico experimentation
by: Bosch, Victoria, et al.
Published: (2025)

Meta-learning In-Context Enables Training-Free Cross Subject Brain Decoding
by: Nan, Mu, et al.
Published: (2026)

BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity
by: Luo, Andrew F., et al.
Published: (2023)

BCI-sift: An automated feature selection toolbox for Brain Computer Interface applications
by: Offenberg, Elena C, et al.
Published: (2026)

ε-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment
by: Hsu, Hao-Lun, et al.
Published: (2024)