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cs.LG2025
Generalization Can Emerge in Tabular Foundation Models From a Single Table
Junwei Ma, Nour Shaheen, Alex Labach +4
Deep tabular modelling increasingly relies on in-context learning where, during inference, a model receives a set of pairs as context and predicts labels for new inputs wit…
cs.LG2024
Diffusion-Based Neural Network Weights Generation
Bedionita Soro, Bruno Andreis, Hayeon Lee +4
Transfer learning has gained significant attention in recent deep learning research due to its ability to accelerate convergence and enhance performance on new tasks. However, its…
cs.LG2024
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova +5
While tabular classification has traditionally relied on from-scratch training, a recent breakthrough called prior-data fitted networks (PFNs) challenges this approach. Similar to…