Predictive Performance

Predictive performance focuses on evaluating and improving the accuracy of models in forecasting future outcomes across diverse domains. Current research emphasizes robust methods that handle data variability and uncertainty, employing techniques like conformal prediction, ensemble methods (e.g., XGBoost), and large language models (LLMs) alongside traditional machine learning algorithms. This field is crucial for advancing various scientific disciplines and practical applications, from optimizing resource allocation in healthcare to enhancing financial forecasting and improving the efficiency of transportation systems.

Papers

August 4, 2023

High-Accuracy Prediction of Metal-Insulator-Metal Metasurface with Deep Learning
Kaizhu Liu, Hsiang-Chen Chui, Changsen Sun, Xue Han
Deep Learning Predictive Performance Metasurface Design Electromagnetic Simulation

August 1, 2023

Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms
Elvis Dohmatob, Meyer Scetbon
Native Robustness Adversarial Robustness Predictive Performance Phase Transition Robust Regression Optimal Trade Learning Norm Fast Minimum Norm Attack Test Time Adversarial

July 11, 2023

Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks
Danny D'Agostino, Ilija Ilievski, Christine Annette Shoemaker
Model Interpretability Predictive Performance Radial Basis Function Gaussian Kernel Active Subspace Precision Matrix Important Feature

July 4, 2023

Human Trajectory Forecasting with Explainable Behavioral Uncertainty
Jiangbei Yue, Dinesh Manocha, He Wang
Bayesian Neural Network Predictive Performance Human Trajectory Diffusion SDE Neural Stochastic Differential Equation Explanation Uncertainty

June 30, 2023

Inter-case Predictive Process Monitoring: A candidate for Quantum Machine Learning?
Stefan Hill, David Fitzek, Patrick Delfmann, Carl Corea
Quantum Machine Learning Quantum Computer Predictive Performance Prediction Accuracy Quantum Machine Learning Model Multiple Candidate Predictive Process Monitoring

June 27, 2023

A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics
Tânia Carvalho, Nuno Moniz, Luís Antunes
Optimization Purpose Procedural Fairness Privacy Policy Machine Learning Application Predictive Performance Data Privacy Knot Theory

June 17, 2023

Predicting Alzheimers Disease Diagnosis Risk over Time with Survival Machine Learning on the ADNI Cohort
Henry Musto, Daniel Stamate, Ida Pu, Daniel Stahl
Human Prediction Time Matter Alzheimer'S Disease Predictive Performance Cognitive Decline ADNI Dataset Dementia Risk

April 17, 2023

Prediction-Oriented Bayesian Active Learning
Freddie Bickford Smith, Andreas Kirsch, Sebastian Farquhar, Yarin Gal, Adam Foster, Tom Rainforth
Active Learning Predictive Performance Information Gain Bayesian Active Learning

April 14, 2023

Uncertainty-Aware Vehicle Energy Efficiency Prediction using an Ensemble of Neural Networks
Jihed Khiari, Cristina Olaverri-Monreal
Neural Network Ensemble Learning Diverse Ensemble Predictive Uncertainty Energy Efficiency Predictive Performance Vehicle Energy Consumption

March 17, 2023

TKN: Transformer-based Keypoint Prediction Network For Real-time Video Prediction
Haoran Li, Pengyuan Zhou, Yihang Lin, Yanbin Hao, Haiyong Xie, Yong Liao
Video Prediction Predictive Performance Prediction Speed Keypoint Prediction

March 6, 2023

On Regression in Extreme Regions
Nathan Huet, Stephan Clémençon, Anne Sabourin
Novel Regression Empirical Risk Minimization Predictive Performance Challenging Environment Prediction Function

February 26, 2023

Performance is not enough: the story told by a Rashomon quartet
Przemyslaw Biecek, Hubert Baniecki, Mateusz Krzyzinski, Dianne Cook
System Performance Supervised Learning Predictive Model Predictive Performance Written Story Effective Model Rashomon Set

January 25, 2023

Evaluating Probabilistic Classifiers: The Triptych
Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan, Peter Vogel
Forecasting Performance Predictive Performance Multiple Outcome Confidence Score Probabilistic Classifier Reliability Diagram

December 27, 2022

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions
Jake C. Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard Zemel
Predictive Performance Probability Pr(E1 Flexible Framework Predictive Algorithm Quantile Temporal Difference Loss Estimation Quantile Estimation

December 22, 2022

A Study of Left Before Treatment Complete Emergency Department Patients: An Optimized Explanatory Machine Learning Framework
Abdulaziz Ahmed, Khalid Y. Aram, Salih Tutun
Study Feature Treatment Effect Metaheuristic Algorithm Predictive Performance Machine Learning Framework Left Leaning Metaheuristic Optimization Algorithm

December 19, 2022

Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding
Ashesh Rambachan, Amanda Coston, Edward Kennedy
Global Evaluation Predictive Performance Predictive Algorithm Robust Performance Unmeasured Confounding Default Prediction Conditional Likelihood

December 12, 2022

Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring
Hué Sullivan, Hurlin Christophe, Pérignon Christophe, Saurin Sébastien
Machine Learning Model Application Proficiency Model Performance Predictive Performance Credit Scoring

December 7, 2022

Fallen Angel Bonds Investment and Bankruptcy Predictions Using Manual Models and Automated Machine Learning
Harrison Mateika, Juannan Jia, Linda Lillard, Noah Cronbaugh, Will Shin
Machine Learning Full Model Predictive Performance Optimal Learning Bankruptcy Prediction Financial Distress

November 30, 2022

Correlation recurrent units: A novel neural architecture for improving the predictive performance of time-series data
Sunghyun Sim, Dohee Kim, Hyerim Bae
Recurrent Neural Network Time Series Forecasting Time Series Data Neural Network Architecture Predictive Performance Recurrent Unit Time Series Decomposition

November 26, 2022

Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance
Mats L. Richter, Christopher Pal
Neural Network Neural Architecture Receptive Field CNN Architecture Predictive Performance

Predictive Performance

Papers

High-Accuracy Prediction of Metal-Insulator-Metal Metasurface with Deep Learning

Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms

Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks

Human Trajectory Forecasting with Explainable Behavioral Uncertainty

Inter-case Predictive Process Monitoring: A candidate for Quantum Machine Learning?

A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics

Predicting Alzheimers Disease Diagnosis Risk over Time with Survival Machine Learning on the ADNI Cohort

Prediction-Oriented Bayesian Active Learning

Uncertainty-Aware Vehicle Energy Efficiency Prediction using an Ensemble of Neural Networks

TKN: Transformer-based Keypoint Prediction Network For Real-time Video Prediction

On Regression in Extreme Regions

Performance is not enough: the story told by a Rashomon quartet

Evaluating Probabilistic Classifiers: The Triptych

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions

A Study of Left Before Treatment Complete Emergency Department Patients: An Optimized Explanatory Machine Learning Framework

Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding

Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring

Fallen Angel Bonds Investment and Bankruptcy Predictions Using Manual Models and Automated Machine Learning

Correlation recurrent units: A novel neural architecture for improving the predictive performance of time-series data

Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance