Latest Research in Machine Learning
31 research papers · 2026 median publication year
Top Research Topics in Machine Learning
- Machine Learning — 6 papers
- EEG and Brain-Computer Interfaces — 5 papers
- Artificial Intelligence — 3 papers
- Stroke Rehabilitation and Recovery — 2 papers
- Computer Vision and Pattern Recognition — 2 papers
- Emotion and Mood Recognition — 2 papers
- Cryptography and Security — 2 papers
- Human-Computer Interaction — 2 papers
- Neurons and Cognition — 1 papers
- Methodology — 1 papers
Highest-Cited Papers
- NeuroSketch: A Practical Design Recipe for Neural Decoding
- Adaptive Anisotropic Attention for Axis-Structured Signals
- Learning aligned EEG representations with subject-specific encoders
- A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyond
- Sparse Bayesian Modeling of EEG Channel Interactions Improves P300 Brain-Computer Interface Performance
- Development of a Mixed-Reality Application for Volitional Step Training in People With Multiple Sclerosis: Cross-Sectional Qualitative User-Centered Co-Design Study
- Standardization of Virtual Reality–Based Exercise Interventions for Reducing Fall Risk in Older Adults
- A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis
- Mind2Cloud: EEG-to-Point Cloud Generation with Two-Granularity Diffusion Decoding
- Conditional Quantum Flow Matching for Data-Scarce Physiological Signal Augmentation
- NeuroStream: spectral-spatio-temporal deep learning for visual stimulus classification from EEG
- Spatial-Frequency Hypergraph Neural Network for EEG-fNIRS Emotion Recognition
- Pretraining for Sample-Efficient Neural Interfaces
- Remote Early Follow‐Up: Home Videos Enabled Reliable General Movement Assessment With Only Weak Association With the Ages and Stages Questionnaire
- EEG-VID: Task-Guided Latent Predictive Pretraining for EEG Decoding and Assistive Target Selection
- NERVE Attacks: Breaking AI-Powered Brain-Computer Interfaces
- Subject-conditioned generative manifold alignment for cross-subject EEG emotion recognition
- Masked Generative-Contrastive Representation Learning for Cross-Dataset EEG-Based Emotion Recognition
- ProCA: Progressive Contrastive Alignment for Robust EEG Visual Decoding
- EEG-based Visual Retrieval and Reconstruction: From Neurally Visible Optimal Layer to Hierarchical Diffusion Generation