All Stories

  1. Marginal Nodes Matter: Towards Structure Fairness in Graphs
  2. Can Data Augmentation Improve Daily Mood Prediction from Wearable Data? An Empirical Study
  3. Meta Graph Learning for Long-tail Recommendation
  4. Ontology-aware Prescription Recommendation in Treatment Pathways Using Multi-evidence Healthcare Data
  5. Harnessing Biomedical Literature to Calibrate Clinicians’ Trust in AI Decision Support Systems
  6. Data heterogeneity in healthcare machine learning models
  7. Workshop on Applied Data Science for Healthcare (DSHealth)
  8. Collaboration Equilibrium in Federated Learning
  9. Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction
  10. GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction
  11. Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility
  12. Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition
  13. Dialogue Based Disease Screening Through Domain Customized Reinforcement Learning
  14. Artificial Intelligence for Drug Discovery
  15. S-LIME
  16. Why Attentions May Not Be Interpretable?
  17. Adversarial Infidelity Learning for Model Interpretation
  18. MoFlow: An Invertible Flow Model for Generating Molecular Graphs
  19. Neural Dynamics on Complex Networks
  20. General-Purpose User Embeddings based on Mobile App Usage
  21. Recent Advances on Graph Analytics and Its Applications in Healthcare
  22. GRAPHENE
  23. Uncovering Pattern Formation of Information Flow
  24. Dynamical Origins of Distribution Functions
  25. MetaPred
  26. Learning From Networks
  27. Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models
  28. Crowdsourcing for Mobile Networks and IoT
  29. Patient Subtyping via Time-Aware LSTM Networks
  30. Healthcare Data Mining with Matrix Models