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From Notes to Musical Form - A Machine Learning Approach

From Notes to Musical Form - A Machine Learning Approach

Added by Emma Wilson

Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population - A machine learning approach

Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population - A machine learning approach

Added by Emma Wilson

Position: Intent-aligned AI Systems Must Optimize for Agency Preservation

Position: Intent-aligned AI Systems Must Optimize for Agency Preservation

Added by Emma Wilson

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides - research article

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides - research article

Added by Emma Wilson

Predicting Methanol Space-Time Yield from CO₂ Hydrogenation Using Machine Learning - Statistical Evaluation of Penalized Regression Techniques

Predicting Methanol Space-Time Yield from CO₂ Hydrogenation Using Machine Learning - Statistical Evaluation of Penalized Regression Techniques

Added by Emma Wilson

Reconstruction of the reversed field pinch magnetic perturbations in toroidal geometry by means of Deep Learning for real-time plasma control - proof of concept for real-time toroidal reconstruction

Reconstruction of the reversed field pinch magnetic perturbations in toroidal geometry by means of Deep Learning for real-time plasma control - proof of concept for real-time toroidal reconstruction

Added by Ava Thompson

Enhancing generalizability of a machine learning model for infrared thermographic defect detection - using 3D numerical modeling

Enhancing generalizability of a machine learning model for infrared thermographic defect detection - using 3D numerical modeling

Added by Emma Wilson

Supporting long-term condition management - a workflow framework for the co-development and operationalization of machine learning models using electronic health record data insights

Supporting long-term condition management - a workflow framework for the co-development and operationalization of machine learning models using electronic health record data insights

Added by Ava Thompson

Continual Learning - Theoretical and Empirical Analysis of Infinitely Wide Neural Networks

Continual Learning - Theoretical and Empirical Analysis of Infinitely Wide Neural Networks

Added by Ava Thompson

On the Impact of Low-Quality Activity Labels in Predictive Process Monitoring - submitted version

On the Impact of Low-Quality Activity Labels in Predictive Process Monitoring - submitted version

Added by Ava Thompson

Machine Learning Prediction of Cardiovascular Risk in Type 1 Diabetes Mellitus Patients Using Radiomics Features Extracted from Eye Images - Master Thesis

Machine Learning Prediction of Cardiovascular Risk in Type 1 Diabetes Mellitus Patients Using Radiomics Features Extracted from Eye Images - Master Thesis

Added by Ava Thompson

Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows

Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows

Added by Ava Thompson

The application of machine learning algorithms for predicting length of stay before and during the COVID-19 pandemic - evidence from Wuhan-area hospitals

The application of machine learning algorithms for predicting length of stay before and during the COVID-19 pandemic - evidence from Wuhan-area hospitals

Added by Ava Thompson

Machine Learning Based Optimization Workflow for Tuning Numerical Settings of Differential Equation Solvers for Boundary Value Problems - Chapter 1 - Abstract and Workflow Overview

Machine Learning Based Optimization Workflow for Tuning Numerical Settings of Differential Equation Solvers for Boundary Value Problems - Chapter 1 - Abstract and Workflow Overview

Added by Ava Thompson

The Impact of the SMOTE Method on Machine Learning and Ensemble Learning Performance Results in Addressing Class Imbalance in Data Used for Predicting Total Testosterone Deficiency in Type 2 Diabetes Patients

The Impact of the SMOTE Method on Machine Learning and Ensemble Learning Performance Results in Addressing Class Imbalance in Data Used for Predicting Total Testosterone Deficiency in Type 2 Diabetes Patients

Added by Ava Thompson