22 citations · 29 across the 7 of their papers we have counts for
7 papers
Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
Olov Holmer, Mattias Krysander, Erik Frisk
Accurate predictions of when a component will fail are crucial when planning maintenance, and by modeling the distribution of these failure times, survival models have shown to be…
Neural Network-Based Piecewise Survival Models
Olov Holmer, Erik Frisk, Mattias Krysander
In this paper, a family of neural network-based survival models is presented. The models are specified based on piecewise definitions of the hazard function and the density functio…
Observer-Based Environment Robust Control Barrier Functions for Safety-critical Control with Dynamic Obstacles
Ying Shuai Quan, Jian Zhou, Erik Frisk +1
This paper proposes a safety-critical controller for dynamic and uncertain environments, leveraging a robust environment control barrier function (ECBF) to enhance the robustness a…
Diffusion-Based Environment-Aware Trajectory Prediction
Theodor Westny, Björn Olofsson, Erik Frisk
The ability to predict the future trajectories of traffic participants is crucial for the safe and efficient operation of autonomous vehicles. In this paper, a diffusion-based gene…
Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory Prediction
Theodor Westny, Joel Oskarsson, Björn Olofsson +1
Given their flexibility and encouraging performance, deep-learning models are becoming standard for motion prediction in autonomous driving. However, with great flexibility comes a…
Energy-Based Survival Models for Predictive Maintenance
Olov Holmer, Erik Frisk, Mattias Krysander
Predictive maintenance is an effective tool for reducing maintenance costs. Its effectiveness relies heavily on the ability to predict the future state of health of the system, and…