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How NOT to benchmark your SITE metric: Beyond Static Leaderboards and Towards Realistic Evaluation
Prabhant Singh, Sibylle Hess, Joaquin Vanschoren
Transferability estimation metrics are used to find a high-performing pre-trained model for a given target task without fine-tuning models and without access to the source dataset.…
A Spatially-Aware Multiple Instance Learning Framework for Digital Pathology
Hassan Keshvarikhojasteh, Mihail Tifrea, Sibylle Hess +2
Multiple instance learning (MIL) is a promising approach for weakly supervised classification in pathology using whole slide images (WSIs). However, conventional MIL methods such a…
Occam's model: Selecting simpler representations for better transferability estimation
Prabhant Singh, Sibylle Hess, Joaquin Vanschoren
Fine-tuning models that have been pre-trained on large datasets has become a cornerstone of modern machine learning workflows. With the widespread availability of online model repo…