This repository is a collection of papers that I personally read and analyzed while preparing for an undergraduate research seminar, along with related presentation and analysis materials (e.g., PPT slides).
- 2025.8.10: Time-MoE: billion scale time series foundation models with mixture of experts
- 2025.8.25: Active feature acquisition via explainability-driven ranking
- 2025.9.15: Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation
- 2025.9.29: Learning of Cluster-based Feature Importance for Electronic Health Record Time-series
- 2025.11.05: HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
- 2025.11.17: Multi-Layer Attention-Based Explainability via Transformers for Tabular Data
- 2025.12.27: Multi-Time Attention Networks for Irregularly Sampled Time Series
- 2026.1.15: Optimizing Long-term Social Welfare in Recommender Systems