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A Data-driven Approach for Heterogeneous Materials Design
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Integrating Machine Learning and Symbolic Reasoning: Learning to Generate Symbolic Representations from Weak Supervision
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Methods for Images, Time Series, and Activation Functions with Deep Neural Networks
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Machine learning approaches towards understanding movement planning in naturalistic settings
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Mining Social Media for Healthcare Intelligence
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Machine Learning for Materials Discovery and Design
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An Adaptive Pattern Recognition Algorithm for a Powered Lower Limb Prosthesis
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Computational Electron Microscopy for the Characterization of Soft, Hard, and Hybrid Materials
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Monitoring Ablation Therapy Using Ensemble Learning Models
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Computational Approaches for Enhanced Metabolomics Annotation and DNA-based Biorecording and Data Storage
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Generalizable Data-driven Models for Personalized Shared Control of Human-Machine Systems
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Design of Tungsten-free, L12-strengthened Cobalt-based Superalloys
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Mutational Processes Modeling and Early Cancer Diagnosis
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Designing Dynamic and Modular Biomolecules and Assays to Interrogate and Control Protein Fate
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Integrating Heterogeneous Traffic Data Sources with High Definition Maps in Autonomous Driving
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Learning from Limited and Imperfect Data in Cyber-Physical System
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Topics in Machine Learning Optimization
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Predictive Traffic Operations and Control of Connected and Automated Vehicle Systems
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Development of Informatics Methods for Analysis of Complex Gene Regulation and Transcriptome Diversity Data in Cancer
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Fisher Score-Based Concept Drift Monitoring and Diagnosis with Applications to Microstructure Nonstationarity Analysis and Deep Learning Segmentation for Multiphase Materials
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Understanding Control of the Shoulder after Stroke Towards Myoelectric Control of Vertical Support to Improve Reach
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Nonequilibrium Dynamics of Soft Materials
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Modeling Bacterial Infection Risk for Data-Driven Antibiotic De-Escalation in Critically Ill Adults
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Digitization for Innovative Platform Design and Advertising
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Towards Understanding Deep Learning via Statistical Physics
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Polymeric Nanomaterials for Photocatalysis and Regenerative Medicine: Integrating Machine Learning and Synthetic Approaches for Materials Design
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Analyzing the Role of Natural Language in Neural-Symbolic Models
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Predicting Employee Engagement: Machine Learning Applications to the Personality-Engagement Link
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Optimization Methods for Scale Invariant Problems in Machine Learning
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Recurrent Neural Network Architectures for Sequence Classification and Explanation
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Model Positionality: A Novel Framework for Data Science with Subjective Target Concepts
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Toward a Digital Twin of Metal Additive Manufacturing: Process Optimization and Control Enabled by Physics-based and Data-driven Models
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