Marija Bezbradica

Adaptation Interfaces for In-Context Tabular Foundation Models in Time-to-Event Prediction

Results indicate that effective TabFM transfer depends on the data regime and on the statistical structure represented by the chosen adaptation interface, and that classification fine-tuning becomes more competitive with zero-shot inference as data sets grow but remains weaker for probabilistic prediction.

Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Clinically Realistic Constraints

MSPCIFormer: A Multi‐Scale Patching Channel‐Independent Transformer for Cryptocurrency Price Forecasting

MSPCIFormer is proposed, a novel Transformer‐based architecture that integrates multi‐scale patching with channel‐independent (CI) modelling to capture heterogeneous temporal dynamics while mitigating noise from time‐varying inter‐asset correlations.