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Enhanced GPIS Learning Based on Local and Global Focus Areas
Implicit surface learning is one of the most widely used methods for 3D surface reconstruction from raw point cloud data. Current …
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The Graph Cut Kernel for Ranked Data
Many algorithms for ranked data become computationally intractable as the number of objects grows due to the complex geometric …
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The Graph Cut Kernel for Ranked Data
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation
Bayesian inference in non-linear dynamical systems seeks to find good posterior approximations of a latent state given a sequence of …
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Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation
Cauchy-Schwarz Regularized Autoencoder
Recent work in unsupervised learning has focused on efficient inference and learning in latent variables models. Training these models …
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Cauchy-Schwarz Regularized Autoencoder
Pathwise Conditioning of Gaussian Processes
As Gaussian processes are used to answer increasingly complex questions, analytic solutions become scarcer and scarcer. Monte Carlo …
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Pathwise Conditioning of Gaussian Processes
GPflux: A Library for Deep Gaussian Processes
We introduce GPflux, a Python library for Bayesian deep learning with a strong emphasis on deep Gaussian processes (DGPs). Implementing …
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Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects
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High-Dimensional Bayesian Optimization with Manifold Gaussian Processes
Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven …
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A Foliated View of Transfer Learning
Transfer learning considers a learning process where a new task is solved by transferring relevant knowledge from known solutions to …
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Estimating Barycenters of Measures in High Dimensions
Barycentric averaging is a principled way of summarizing populations of measures. Existing algorithms for estimating barycenters …
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