Asiful Arefeen
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    • Counterfactual Explainable Recommendation
    • Adversarial Counterfactual Visual Explanations
    • CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
    • Generating Interpretable Counterfactual Explanations By Implicit Minimization of Epistemic and Aleatoric Uncertainties
    • Counterfactual Explanations for Multivariate Time Series
    • Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
    • Forecasting the future clinical events of a patient through contrastive learning
    • Feature Importance Explanations for Temporal Black-Box Models
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    • Augmented Experiment in Material Engineering Using Machine Learning
    • Computational Framework for Sequential Diet Recommendation: Integrating Linear Optimization and Clinical Domain Knowledge
    • Local Interpretable Model-Agnostic Explanations
    • Characterizing Decision Boundary for DNN on High Dimensional Data
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    • Boosting Lying Posture Classification with Transfer Learning
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    • Paper Review: Attention is All You Need.
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    • U-Net: Convolutional Networks for Biomedical Image Segmentation
    • Social and competition stress detection with wristband physiological signals
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    • BMI 310: App Development for Population Health
    • BMI 502: Foundations of BMI Methods
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    • Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations
    • GlucoseAssist: Personalized Blood Glucose Level Predictions and Early Dysglycemia Detection
    • GlySim: Modeling and Simulating Glycemic Response for Behavioral Lifestyle Interventions
    • Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced Error
    • Use of Machine Learning to Predict Medication Adherence in Individuals at Risk for Atherosclerotic Cardiovascular Disease
    • Computational Framework for Sequential Diet Recommendation: Integrating Linear Optimization and Clinical Domain Knowledge
    • Forewarning Postprandial Hyperglycemia with Interpretations using Machine Learning
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🎉 Easily create your own simple yet highly customizable blog

Oct 27, 2023 · 1 min read
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Last updated on Oct 27, 2023
Asiful Arefeen
Authors
Asiful Arefeen
PhD Candidate
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