Sequence Search uses neural architecture search and a differentiable Bloch simulator to automatically create and optimize MRI pulse sequences that satisfy given design goals.
Knowledge- based systems212, 106622 (2021)
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The yvsoucom-iterkit framework demonstrates that healthcare risk prediction pipelines have a structured search space dominated by a small set of high-impact components such as augmentation and imbalance handling, with substantial redundancy among variants.
An evolutionary search framework auto-configures multi-scale bi-branch CNNs to generate Pareto fronts of error-versus-complexity models for multi-output time-series forecasting.
FLIM-BoFP replaces per-block patch clustering in FLIM networks with a single input-level clustering step that creates a bag of feature points used to define filters across all encoder blocks, yielding faster training for parasite detection in optical microscopy.
citing papers explorer
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Sequence Search: Automated Sequence Design using Neural Architecture Search
Sequence Search uses neural architecture search and a differentiable Bloch simulator to automatically create and optimize MRI pulse sequences that satisfy given design goals.
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A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction
The yvsoucom-iterkit framework demonstrates that healthcare risk prediction pipelines have a structured search space dominated by a small set of high-impact components such as augmentation and imbalance handling, with substantial redundancy among variants.
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Auto-Configured Networks for Multi-Scale Multi-Output Time-Series Forecasting
An evolutionary search framework auto-configures multi-scale bi-branch CNNs to generate Pareto fronts of error-versus-complexity models for multi-output time-series forecasting.
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FLIM Networks with Bag of Feature Points
FLIM-BoFP replaces per-block patch clustering in FLIM networks with a single input-level clustering step that creates a bag of feature points used to define filters across all encoder blocks, yielding faster training for parasite detection in optical microscopy.