Loss Functions - Edgentiq

The Statistical Backbone of Neural Networks: Why Activation and Loss Functions Matter

Physics-Informed Machine Learning: New Energy Loss Functions Improve Scientific Predictions

Safeguarding Generative AI with Confidence-Aware Training

Maintaining Data Structure in Reduced Dimensions with Relationship Preserving Loss

Enhancing Small Object Detection Through Inter-Class Spatial Relationships

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A Critical Look at Skeleton-Recall Loss for Tubular Structure Segmentation

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Optimizing Top-K Ranking in Recommender Systems with SoftmaxLoss@K

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Improving SAR Ship Identification Through Classification-Guided Image Enhancement

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LoReUn: A Smarter Approach to Machine Unlearning Through Data Loss Cues

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Mapping the Landscape of Preference Optimization: A Unified Theoretical Framework for DPO

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Rethinking Instruction Tuning: The Impact of Prompt and Response Token Weighting

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Unlocking Performance in Remote Sensing Change Detection: A Focus on Fundamental Design Choices

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The Statistical Backbone of Neural Networks: Why Activation and Loss Functions Matter

November 10, 2025

Physics-Informed Machine Learning: New Energy Loss Functions Improve Scientific Predictions

November 5, 2025

Safeguarding Generative AI with Confidence-Aware Training

September 13, 2025