[PDF] Top 20 Learning corrections for hyperelastic models from data
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Learning corrections for hyperelastic models from data
... laws from data is seen as the ultimate sign of human ...machine learning community, some recent works have attempted to simply substitute physical laws by ...are models whose validity and ... Voir le document complet
13
Demonstrating and Learning Multimodal Socio-communicative Behaviors for HRI: Building Interactive Models from Immersive Teleoperation Data
... Machine learning is now widely used to extract such intel- ligence from ...interactive data is thus a major issue for fostering AI for ...HRI data without actually disposing of ... Voir le document complet
6
Learning aspect models with partially labeled data
... researcher from Symantec concluded that for some of the company’s large production projects, the approach has yielded a good return on investment ... Voir le document complet
7
Probabilistic relational models learning from graph databases
... stores data structured as ...complex data, while remaining intuitive and simple for the ...development for 10 years and in production for over 7 ...efficient for handling node ... Voir le document complet
154
Evolutive deep models for online learning on data streams with no storage
... designed for effective knowledge transfer across multiple sequentially arriving ...showed for the reinforcement learning problems, but the authors state its possible application to a wide range of ... Voir le document complet
12
Learning representations from functional MRI data
... consider data from functional Magnetic Resonance Imaging ( fMRI ), that we study in a machine learning setting: we learn a model of brain activity that should generalize on unseen ...fMRI data ... Voir le document complet
183
Benchmark estimates for aboveground litterfall data derived from ecosystem models
... Machine learning methods are independent of the relationships between response variables and pre- dictive variables, especially when compared with tra- ditional empirical models such as linear regression ... Voir le document complet
14
Learning from genomic data : efficient representations and algorithms.
... role for the generalisation ability of the model, allows to obtain more interpretable PRS than other models such as ridge ...search for missing heritability, which may be due to ...features ... Voir le document complet
145
Model order reduction for hyperelastic materials
... coming from previously computed, detailed models (in this frameworks, the work by Ryckelyck [11] is an ...exception). From this information, the most relevant structures of these results are computed ... Voir le document complet
28
Learning spatiotemporal trajectories from manifold-valued longitudinal data
... framework for the definition and estimation of mixed- effects models for longitudinal manifold-valued ...the data and problem to deal ...the data in a spatial and a temporal ...[2], ... Voir le document complet
10
Learning Multicriteria Fuzzy Classification Method PROAFTN from Data
... preference models from examples has been very ...machine learning also use pre-assigned examples known as training set to infer the parameters of classification ...trees from examples [14-15] ... Voir le document complet
20
Incremental Bayesian network structure learning from data streams
... graphical models are introduced by Jordan as: Graphical models, a marriage between probability theory and graph theory, provide a natural tool for dealing with two problems that occur throughout ... Voir le document complet
215
EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions
... (EP) models achieved good progress in simulating cardiac electrical ...deep learning methods achieved impressive results but suffer from robustness issues in healthcare due to their lack of ... Voir le document complet
10
Learning to rank from medical imaging data
... chosen for its widespread use as a regression technique applied to fMRI ...the data and the target values, we also selected a non-linear regression model: support vector regression (SVR) with a Gaussian ... Voir le document complet
10
Learning possibilistic networks from data: a survey.
... tools for mod- elling and reasoning, especially in the presence of imprecise and/or uncertain ...graphical models have been successfully used in sev- eral real ...to learning possibilis- tic networks ... Voir le document complet
9
Learning from ranking data : theory and methods
... Ranking data naturally appears in a wide variety of situations, especially when the data comes from human activities: ballots in political elections, survey answers, competition results, cus- tomer ... Voir le document complet
210
Robust supervised classification with mixture models: Learning from data with uncertain labels
... Noise modelling. Among all these solutions, the model proposed in [18] by Lawrence et al. has the advantage of explicitely including the label noise in the model with a sound theoretical foundation in the binary ... Voir le document complet
27
Haptic Rendering of Hyperelastic Models with Friction
... especially for their applications in educational and learning processes for surgical ...way for the surgeon to be in contact with anatomical parts, it is essential for simulators to ... Voir le document complet
7
Hybrid constitutive modeling: data-driven learning of corrections to plasticity models
... of data-driven techniques to avoid the employ of phenomenological constitutive ...general, data do not fit perfectly to existing models, and present deviations from the most popular ones, we ... Voir le document complet
10
Constructing learning models from data : the dynamic catalog mailing problem
... more data for improving estimates of the model param- ...online learning” procedure. Will a carefully designed “batch online learning” algorithm converge to something of interest? Before ... Voir le document complet
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