11 papers
Functional MRI Time Series Generation via Wavelet-Based Image Transform and Spectral Flow Matching for Brain Disorder Identification
Hwa Hui Tew, Junn Yong Loo, Fang Yu Leong +6
Functional Magnetic Resonance Imaging (fMRI) provides non-invasive access to dynamic brain activity by measuring blood oxygen level-dependent (BOLD) signals over time. However, the…
KnowDiffuser: A Knowledge-Guided Diffusion Planner with LLM Reasoning
Fan Ding, Xuewen Luo, Fengze Yang +4
Recent advancements in Language Models (LMs) have demonstrated strong semantic reasoning capabilities, enabling their application in high-level decision-making for autonomous drivi…
T2I-Diff: fMRI Signal Generation via Time-Frequency Image Transform and Classifier-Free Denoising Diffusion Models
Hwa Hui Tew, Junn Yong Loo, Yee-Fan Tan +5
Functional Magnetic Resonance Imaging (fMRI) is an advanced neuroimaging method that enables in-depth analysis of brain activity by measuring dynamic changes in the blood oxygenati…
Drive As You Like: Multi-Head Diffusion with Reinforcement Learning for Personalized Driving
Fan Ding, Xuewen Luo, Fucai Ke +6
Despite significant progress, imitation learning-based autonomous driving planners remain largely restricted to reproducing high-frequency biased behaviors, overlooking the inheren…
GSMT: Graph Fusion and Spatiotemporal TaskCorrection for Multi-Bus Trajectory Prediction
Fan Ding, Hwa Hui Tew, Junn Yong Loo +6
Accurate trajectory prediction for buses is crucial in intelligent transportation systems, particularly within urban environments. In developing regions where access to multimodal…
Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching
Junn Yong Loo, Michelle Adeline, Julia Kaiwen Lau +6
Energy-based models (EBMs) are a powerful class of probabilistic generative models due to their flexibility and interpretability. However, relationships between potential flows and…