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stat.ML2025
From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning
Zhe Huang, Simone Rossi, Rui Yuan +1
Transformers have become a standard architecture in machine learning, demonstrating strong in-context learning (ICL) abilities that allow them to learn from the prompt at inference…
stat.ML2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective
Simone Rossi, Ankit Singh, Thomas Hannagan
The elusive nature of gradient-based optimization in neural networks is tied to their loss landscape geometry, which is poorly understood. However recent work has brought solid evi…