7 citations · 19 across the 19 of their papers we have counts for
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cs.LG2023
Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings
Tobias Weber, Michael Ingrisch, Bernd Bischl +1
Purpose: To analyze and remove protected feature effects in chest radiograph embeddings of deep learning models. Methods: An orthogonalization is utilized to remove the influence o…
cs.CL2023
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models
Zheyu Zhang, Han Yang, Bolei Ma +2
Large Language Models (LLMs) demonstrate remarkable performance on a variety of natural language understanding (NLU) tasks, primarily due to their in-context learning ability. This…
stat.CO2023
mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression with Adaptive First-order Methods
David Rügamer
This paper presents a high-level description of the R software package mixdistreg to fit mixture of experts distributional regression models. The proposed framework is implemented…