Efficient Prediction

Efficient prediction focuses on developing methods that accurately forecast future outcomes while minimizing computational cost and resource consumption. Current research emphasizes improving model efficiency through techniques like adaptive basis function selection, information bottleneck methods for feature reduction, and the use of hybrid 2.5D architectures in image analysis, alongside advancements in time series forecasting and multi-agent trajectory prediction. These improvements are crucial for deploying predictive models in resource-constrained environments and for enhancing the explainability and fairness of predictions across diverse applications, including healthcare, finance, and process monitoring.

Papers

November 15, 2024

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing
Andrea Alfarano, Alberto Alfarano, Linda Friso, Andrea Bacciu, Irene Amerini, Fabrizio Silvestri
LeArning Abstract Convolutional Neural Network Temporal Modeling Traditional Convolutional Spatio Temporal Learning Depth Wise Convolution Efficient Prediction Convolutional Neural Network Based Framework Spatio Temporal Predictive Learning

October 4, 2024

Topology-Informed Machine Learning for Efficient Prediction of Solid Oxide Fuel Cell Electrode Polarization
Maksym Szemer, Szymon Buchaniec, Tomasz Prokop, Grzegorz Brus
Microstructure Model Topological Learning Electrode Array Microstructural Image Fuel Cell Efficient Prediction

August 14, 2024

Adaptive Basis Function Selection for Computationally Efficient Predictions
Anton Kullberg, Frida Viset, Isaac Skog, Gustaf Hendeby
Gaussian Process Function Approximation Prediction Accuracy Basis Function Efficient Prediction

June 7, 2024

TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks
Ninghui Feng, Songning Lai, Fobao Zhou, Zhenxiao Yin, Hang Zhao
Time Series Forecasting Information Bottleneck Temporal Dynamic Efficient Prediction Time Series Forecasting Model

April 19, 2024

Explainable AI for Fair Sepsis Mortality Predictive Model
Chia-Hsuan Chang, Xiaoyang Wang, Christopher C. Yang
Explainable AI Predictive Model Predictive Performance Sepsis Prediction Efficient Prediction Sepsis Treatment

February 15, 2024

Tracking Changing Probabilities via Dynamic Learners
Omid Madani
Learning Rate Relative Probability Dynamic Learning Deodata Predictor Class Prediction Efficient Prediction

July 26, 2023

ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptation
Görkay Aydemir, Adil Kaan Akan, Fatma Güney
Trajectory Prediction Adaptation Concern Multi Agent Trajectory Prediction Efficient Prediction Adaptive Prediction Aligned Action Prompt Endpoint Prediction

July 25, 2023

Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT
Taha Emre, Marzieh Oghbaie, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunović
Optical Coherence Tomography 3D Deep Learning Efficient Prediction

July 17, 2023

Efficient Prediction of Peptide Self-assembly through Sequential and Graphical Encoding
Zihan Liu, Jiaqi Wang, Yun Luo, Shuang Zhao, Wenbin Li, Stan Z. Li
Sequential Information Peptide Source Efficient Prediction Signal Peptide

July 12, 2023

Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoring
Andreas Metzger, Tristan Kley, Aristide Rothweiler, Klaus Pohl
Adaptation Concern Prediction Accuracy accuratE Prediction Prescriptive Process Monitoring Efficient Prediction

February 16, 2022

XAI in the context of Predictive Process Monitoring: Too much to Reveal
Ghada Elkhawaga, Mervat Abuelkheir, Manfred Reichert
Context Information xAI Community Process Mining eXplainable Artificial Intelligence Predictive Process Monitoring Explainability Technique Efficient Prediction