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Robustly Parameterised Higher-Order Probabilistic Models

Fredrik Dahlqvist, Vincent Danos, Ilias Garnier, Marc Herbstritt
2016 International Conference on Concurrency Theory  
We present a method for constructing robustly parameterised families of higher-order probabilistic models.  ...  Naturality ensures that parameterised models are invariant by change of granularity -ie that parameterisations are intrinsic.  ...  The characterisation of objects of Pol cz can be formulated as follows: 23:4 Robustly Parameterised Higher-Order Probabilistic Models The family of zero-dimensionalisations of a space X indexed by all  ... 
doi:10.4230/lipics.concur.2016.23 dblp:conf/concur/DahlqvistDG16 fatcat:x4y5hb4npbd2xdtwilpowix2nq

Robustly Parameterised Higher-Order Probabilistic Models *

Fredrik Dahlqvist, Vincent Danos, Ilias Garnier
unpublished
We present a method for constructing robustly parameterised families of higher-order probab-ilistic models.  ...  Continuity ensures that models are robust with respect to their parameterisation.  ...  The characterisation of objects of Pol cz can be formulated as follows: 23:4 Robustly Parameterised Higher-Order Probabilistic Models The family of zero-dimensionalisations of a space X indexed by all  ... 
fatcat:et2s4hxdtzaejebtkupxtqi4ji

CAD based shape optimization for gas turbine component design

Djordje Brujic, Mihailo Ristic, Massimiliano Mattone, Paolo Maggiore, Gian Paolo De Poli
2009 Structural And Multidisciplinary Optimization  
This shape change can be realised by modifying the parameter values of a suitably parameterised Computer Aided Design (CAD) model.  ...  In order to improve product characteristics, engineering design makes increasing use of Robust Design and Multidisciplinary Design Optimisation.  ...  The first step is the construction of a parameterised CAD model.  ... 
doi:10.1007/s00158-009-0442-9 fatcat:zn4kwfseuzhmjilsodf7gtru7i

Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface

Keith Beven, Hannah Cloke, Florian Pappenberger, Rob Lamb, Neil Hunter
2014 Science China. Earth Sciences  
There is a strong drive towards hyperresolution earth system models in order to resolve finer scales of motion in the atmosphere.  ...  This paper discusses these issues in more detail with specific reference to land surface parameterisations and flood inundation models.  ...  Introduction It is a general expectation in earth system science modelling that we will continue to move to higher and higher resolution coupled models, with so called hyperresolution models (on the order  ... 
doi:10.1007/s11430-014-5003-4 fatcat:h2oib5lkbjgltm4dxt2v2nug34

Consensus between Pipelines in Structural Brain Networks

Christopher S. Parker, Fani Deligianni, M. Jorge Cardoso, Pankaj Daga, Marc Modat, Michael Dayan, Chris A. Clark, Sebastien Ourselin, Jonathan D. Clayden, Yong Liu
2014 PLoS ONE  
We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines.  ...  This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study.  ...  Both reconstructions had similar capabilities but varied with respect to the details of the cortical parcellation, registration and probabilistic fiber model method.  ... 
doi:10.1371/journal.pone.0111262 pmid:25356977 pmcid:PMC4214749 fatcat:hllkwt27yfacnapctjz46rt7gy

Multi-view Probabilistic Segmentation of Pome Fruit with a Low-Cost RGB-D Camera [chapter]

Pablo Ramon Soria, Fouad Sukkar, Wolfram Martens, B. C. Arrue, Robert Fitch
2017 Advances in Intelligent Systems and Computing  
Furthermore, the model provides probabilistic reconstruction of the entire apple which can be used for better grasping of the fruit.  ...  In order to perform this task, robots should be able to recognize and segment fruit in their perceptual environment.  ...  In order to achieve better results in the probabilistic segmentation we perform registration of point clouds taken from multiple points of view.  ... 
doi:10.1007/978-3-319-70836-2_27 fatcat:2gynn2grubgpvo7tsm7vnv4loa

Modelling Non-stationary and Non-separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution [chapter]

Lorenzi Marco, Gabriel Ziegler, Daniel C. Alexander, Sebastien Ourselin
2015 Lecture Notes in Computer Science  
The proposed model is parameterised by a sparse set of control points independently identified by specific spatial and temporal parameters.  ...  These assumptions are often made in order to lead to computationally tractable approaches to longitudinal modelling, but inevitably lead to an oversimplification of the complex spatial and temporal dynamics  ...  In fact, flexible modelling instruments are required in order to robustly capture meaningful pathological accelerations specific to sensitive brain regions.  ... 
doi:10.1007/978-3-319-27929-9_4 fatcat:df2cpqnwoberleedwktflamlve

Social Motorics – Towards an Embodied Basis of Social Human-Robot Interaction [chapter]

Amir Sadeghipour, Ramin Yaghoubzadeh, Andreas Rüter, Stefan Kopp
2009 Cognitive Systems Monographs  
Based on an unified sensorimotor representation, it integrates hierarchical motor knowledge structures, probabilistic forward models for predicting observations, and inverse models for motor learning.  ...  In this paper we present a biologically-inspired model for social behavior recognition and generation.  ...  With a focus on hand-arm gestures, we describe a probabilistic model that exploits hierarchical motor structures with forward and inverse models in order to allow resonance-based processing of social behavior  ... 
doi:10.1007/978-3-642-10403-9_20 fatcat:oemljdrnovdzpkhjxm35hevbd4

Stable Implementation of Probabilistic ODE Solvers [article]

Nicholas Krämer, Philipp Hennig
2020 arXiv   pre-print
Using all three techniques enables numerical computation of probabilistic solutions of ODEs with algorithms of order up to 11, as demonstrated on a set of challenging test problems.  ...  The resulting rapid convergence is shown to be competitive to high-order, state-of-the-art, classical methods.  ...  The underlying ODE is the Lotka-Volterra model in the parameterisation from the experiments below.  ... 
arXiv:2012.10106v1 fatcat:nsrhmvxtynfyddufzmmrd4h3qa

A Probabilistic Background Model for Tracking [chapter]

J. Rittscher, J. Kato, S. Joga, A. Blake
2000 Lecture Notes in Computer Science  
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow.  ...  This model functions as a low level process for a car tracker. A particle filter is employed as a stochastic filter for the car tracker.  ...  In order to track the cars robustly it is necessary to detect the shadows as well as the cars. Fig. 2 . 2 Intensity histograms of the different regions.  ... 
doi:10.1007/3-540-45053-x_22 fatcat:sg6n53yu7ndhdb3bunxgmmxwcy

MIXED PROBABILITY MODELS FOR ALEATORIC UNCERTAINTY ESTIMATION IN THE CONTEXT OF DENSE STEREO MATCHING

Z. Zhong, M. Mehltretter
2021 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
To allow a fair comparison, we adapt a common neural network architecture to investigate the effects of the different uncertainty models.  ...  To overcome this limitation, we propose two novel mixed probability models consisting of Laplacian and Uniform distributions for the task of aleatoric uncertainty estimation.  ...  in Section 5.2, in order to verify the validity of the proposed uncertainty models.  ... 
doi:10.5194/isprs-annals-v-2-2021-17-2021 fatcat:5fiqd73nq5erte536gcujp65y4

On the probabilistic epipolar geometry

Sami S. Brandt
2008 Image and Vision Computing  
We will thus have a point-probability-density relation which can be understood as a probabilistic form of the epipolar constraint; it also approaches the true point-line relation as the number of training  ...  Derivation of the Probabilistic Epipolar Constraint In this section, we will further develop the considerations presented in Section 2 and derive the probabilistic epipolar constraint.  ...  The fundamental matrix and its covariance matrix were automatically robustly estimated from point correspondences as proposed in [1, 2] .  ... 
doi:10.1016/j.imavis.2006.12.002 fatcat:h53r2i3xufay3ebxefnecnyvmu

On the Probabilistic Epipolar Geometry

S. S. Brandt
2004 Procedings of the British Machine Vision Conference 2004  
We will thus have a point-probability-density relation which can be understood as a probabilistic form of the epipolar constraint; it also approaches the true point-line relation as the number of training  ...  Derivation of the Probabilistic Epipolar Constraint In this section, we will further develop the considerations presented in Section 2 and derive the probabilistic epipolar constraint.  ...  The fundamental matrix and its covariance matrix were automatically robustly estimated from point correspondences as proposed in [1, 2] .  ... 
doi:10.5244/c.18.13 dblp:conf/bmvc/Brandt04 fatcat:5lim6x24o5buddsnlubjmpkfv4

Predicting the causative pathogen among children with pneumonia using a causal Bayesian network [article]

Yue Wu, Steven Mascaro, Mejbah Bhuiyan, Parveen Fathima, Ariel O. Mace, Mark P. Nicol, Peter Richmond, Lea-Ann Kirkham, Michael Dymock, David A. Foley, Charlie McLeod, Meredith L. Borland (+5 others)
2022 medRxiv   pre-print
both domain expert knowledge and numerical data.MethodsWe used domain expert knowledge and data in combination and iteratively, to construct, parameterise and validate a causal BN to predict causative  ...  Causal Bayesian networks (BNs) serve as powerful tools for this problem as they provide clear maps of probabilistic relationships between variables and produce results in an explainable way by incoporating  ...  the model as a series of conditional probability tables (CPTs), i.e., parameterisation.  ... 
doi:10.1101/2022.07.01.22277170 fatcat:acaxpsyuzvfrdksbpupyuah6wm

Negative feedback may suppress variation to improve collective foraging performance [article]

Andreagiovanni Reina, James A. R. Marshall
2020 bioRxiv   pre-print
Introduction Collectively-foraging social insects need to use feedback mechanisms in order to robustly and efficiently satisfy the nutritional requirements of the colony.  ...  The model with negative feedback, however, requires a heuristic individual parameterisation based on site qualities, which we perform numerically (see Supplementary Text).  ...  This is supplemented by a notebook for MuMoT [42] , an open-source tool for multiscale modelling, which reproduces similar results to those presented herein.  ... 
doi:10.1101/2020.04.21.053074 fatcat:keqcwonsozdenbkm4s65uqx3qe
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