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cs.LG2026
Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation
Mihai Suteu, Ovidiu Serban
Deep ensembles provide the most reliable uncertainty estimates in deep learning, but their cost grows linearly with the number of members. Implicit ensembles lower this cost by sha…
cs.LG2025
Simplifying Multi-Task Architectures Through Task-Specific Normalization
Mihai Suteu, Ovidiu Serban
Multi-task learning (MTL) aims to leverage shared knowledge across tasks to improve generalization and parameter efficiency, yet balancing resources and mitigating interference rem…
cs.LG2023★ 1 cited
A novel approach for predicting epidemiological forecasting parameters based on real-time signals and Data Assimilation
Romain Molinas, César Quilodrán Casas, Rossella Arcucci +1
This paper proposes a novel approach to predict epidemiological parameters by integrating new real-time signals from various sources of information, such as novel social media-base…