24 papers · ranked by Valyu relevance
Ziran Ding, Yu Liu, Jun Liu, Kaimin Yu + 3 more
'Peiliang Jing' 'You He'] Networked multiple sensors are used to solve the problem of maneuvering target tracking. To avoid the linearization of nonlinear dynamic functions, and to obtain more accurate estimates for maneuvering targets, a novel adaptive information-weighted consensus filter for maneuvering target…
Wei Zhu, Wei Wang, Gannan Yuan, Xue-Bo Jin
In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm…
Xiaohong Liu, Xulong Zhao, Gang Liu, Zili Wu + 3 more
Multiple Model Filter Authors: ['Xiaohong Liu' 'Xulong Zhao' 'Gang Liu' 'Zili Wu' 'Tao Wang' 'Lei Meng' 'Yuhan Wang'] Abstract— 3D Multi-Object Tracking (MOT) provides the trajectories of surrounding objects, assisting robots or vehicles in smarter path planning and obstacle avoidance. Existing 3D MOT methods based on…
Sebastian Dingler
—For model-based estimation methods, the modeling that is as close to reality as possible makes a vital estimation result. In simple applications, it is sufficient to model a system with a single state-space model. However, there are applications in which a system changes its behavior deterministically or…
Gilles Eerlings, Sebe Vanbrabant, Jori Liesenborgs, Gustavo Rovelo Ruiz + 2 more
Informed and Transparent Decision-Making Authors: ['Gilles Eerlings' 'Sebe Vanbrabant' 'Jori Liesenborgs' 'Gustavo Rovelo Ruiz' 'Davy Vanacken' 'Kris Luyten'] Abstract. We present an approach, AI-Spectra, to leverage model multiplicity for interactive systems. Model multiplicity means using slightly different AI models…
Joshua I. Glaser, Matthew Whiteway, John P. Cunningham, Liam Paninski + 1 more
Modern recording techniques can generate large-scale measurements of multiple neural populations over extended time periods. However, it remains a challenge to model non-stationary interactions between high-dimensional populations of neurons. To tackle this challenge, we develop recurrent switching linear dynamical…
Qingyan Xiang, Yubai Yuan, Dongyuan Song, Usman J. Wudil + 3 more
'Muktar H. Aliyu' 'C. William Wester' 'Bryan E. Shepherd'] > Causal inference literature has extensively focused on binary treatments, with relatively fewer methods developed for multi-valued treatments. In particular, methods for multiple simultaneously assigned treatments remain understudied despite their practical…
Luca Serena, Moreno Marzolla, Gabriele D’Angelo, Stefano Ferretti
—Multilevel modeling and simulation (M&S) is becoming increasingly relevant due to the benefits that this methodology offers. Multilevel models allow users to describe a system at multiple levels of detail. From one side, this can make better use of computational resources, since the more detailed and time-consuming…
J. Crossa, J. Sun, A. Montesinos‐López, P. Pérez‐Rodríguez + 4 more
The rapid expansion of genomic, environmental, phenomic, and other high-dimensional data sources has transformed genomic prediction in plant breeding. However, the terms multimodal, interaction modeling, and multimodule architecture are often used inconsistently, generating ambiguity regarding whether they refer to…
Eivind F. Kleiven, Frédéric Barraquand, Olivier Gimenez, John-André Henden + 3 more
Occupancy models have been extended to account for either multiple spatial scales or species interactions in a dynamic setting. However, as interacting species (e.g., predators and prey) often operate at different spatial scales, including nested spatial structure might be especially relevant to models of interacting…
Zhixiao Zhu, Maria Christodoulou, David Steinsaltz
Many complex systems are modelled using modular models, where individual sub-models are estimated separately and then combined. While this simplifies inference, it fails to account for interactions between components. A natural solution is to estimate all components jointly, but this is often impractical due to…
Zaynab Hammoud, Frank Kramer
Simple Summary In biological terms, the term "pathway" is used to describe a collection of processes within a cell that lead to one or more actions. The graphical representation of these processes enables the reader to understand complex relationships and interactions much more easily compared to free-text…
Michael Tsang, James Enouen, Yan Liu
Deep learning, alongside other modern machine learning techniques, has become the state of the art solution for a diverse range of real-world tasks. These include a variety of sensitive applications such as healthcare, finance, autonomous driving, criminal justice, and others which all pose significant concerns for…
Theresa Ramelot, Roberto Tejero, Gaetano Montelione
Biomolecules exhibit dynamic behavior that single-state models of their structures cannot fully capture. We review some recent advances for investigating multiple conformations of biomolecules, including experimental methods, molecular dynamics simulations, and machine learning. We also address the challenges…
V. K. B. Kota
In nuclei with valence nucleons are say identical nucleons and say these nucleons occupy several-j orbits, then it is possible to consider pair creation operator S+ to be a sum of the single-j shell pair creation operators S+(j) with arbitrary phases, S+ = P j αjS+(j); αj = ±1. In this situation, it is possible to…
Zexian Zeng, Xia Jiang, Richard Neapolitan
Background The problem of learning causal influences from data has recently attracted much attention. Standard statistical methods can have difficulty learning discrete causes, which interacting to affect a target, because the assumptions in these methods often do not model discrete causal relationships well. An…
Bruno Stegani, Emanuele Scalone, Fran Bacic Toplek, Thomas Lohr + 4 more
The computational study of the binding of a ligand to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of in silico drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by…
Viola Merhof, Thorsten Meiser
Responding to rating scale items is a multidimensional process, since not only the substantive trait being measured but also additional personal characteristics can affect the respondents’ category choices. A flexible model class for analyzing such multidimensional responses are IRTree models, in which rating responses…
Christopher Schölzel, Valeria Blesius, Gernot Ernst, Andreas Dominik
Reproducible, understandable models that can be reused and combined to true multi-scale systems are required to solve the present and future challenges of systems biology. However, many mathematical models are still built for a single purpose and reusing them in a different context can be challenging due to an…
Leif Jacobson, James Stevenson, Farhad Ramezanghorbani, Steven Dajnowicz + 1 more
Transferable neural network potentials have shown great promise as an avenue to increase the accuracy and applicability of existing atomistic force fields for organic molecules and inorganic materials. Training sets used to develop transferable potentials are very large, typically millions of examples, and as such, are…
Helle W. van den Maagdenberg, Martin Šícho, David Alencar Araripe, Sohvi Luukkonen + 9 more
Building reliable and robust quantitative structure-property relationship (QSPR) models is a challenging task. First, the experimental data needs to be obtained, analyzed and curated. Second, the number of available methods is continuously growing and evaluating different algorithms and methodologies can be arduous.…
Hyemin Han
In the present study, I developed and tested an R module to explore the best models within the context of multilevel modeling in research in public health. The module that I developed, explore.models, compares all possible candidate models generated from a set of candidate predictors with information criteria, Akaike…
Prashanth Athri, Vidhya Murali, Pradyumna Y Muralidhar, Cassandra Königs + 4 more
- 1. Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India - 2. PES Center for Pattern Recognition, Department of Computer Science and Engineering, PES University, Bengaluru, India - 3. Bioinformatics and Medical Informatics, Bielefeld University…
Andrew Phillips, Anusha Srinivas, Ilina Prentoska Prentoska, Margaret O'Dea + 5 more
Teaching chemistry and chemical engineering students about biologics formulation remains challenging despite its increasing importance in pharmaceutical development. Monoclonal antibodies, commonly called mAbs, are the most popular biologics. They have been developed into drugs to treat various diseases in the past…