3 papers
cs.LG2026
A Kinetic Energy Perspective of Flow Matching
Ziyun Li, Huancheng Hu, Soon Hoe Lim +6
Flow-based generative models can be viewed through a physics lens: sampling transports a particle from noise to data by integrating a learned velocity field, and each sample corres…
cs.LG2025
Prediction via Shapley Value Regression
Amr Alkhatib, Roman Bresson, Henrik Boström +1
Shapley values have several desirable, theoretically well-supported, properties for explaining black-box model predictions. Traditionally, Shapley values are computed post-hoc, lea…
cs.LG2024
Interpretable Graph Neural Networks for Heterogeneous Tabular Data
Amr Alkhatib, Henrik Boström
Many machine learning algorithms for tabular data produce black-box models, which prevent users from understanding the rationale behind the model predictions. In their unconstraine…