
HyperCube: Implicit Field Representations of Voxelized 3D Models
Recently introduced implicit field representations offer an effective wa...
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Efficient GPU implementation of randomized SVD and its applications
Matrix decompositions are ubiquitous in machine learning, including appl...
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Flowbased SVDD for anomaly detection
We propose FlowSVDD – a flowbased oneclass classifier for anomaly/outl...
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HyperColor: A HyperNetwork Approach for Synthesizing Autocolored 3D Models for Game Scenes Population
Designing a 3D game scene is a tedious task that often requires a substa...
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Modeling 3D Surface Manifolds with a Locally Conditioned Atlas
Recently proposed 3D object reconstruction methods represent a mesh with...
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HyperPocket: Generative Point Cloud Completion
Scanning reallife scenes with modern registration devices typically giv...
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RegFlow: Probabilistic Flowbased Regression for Future Prediction
Predicting future states or actions of a given system remains a fundamen...
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Processing of incomplete images by (graph) convolutional neural networks
We investigate the problem of training neural networks from incomplete i...
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Flowbased anomaly detection
We propose OneFlow  a flowbased oneclass classifier for anomaly (outl...
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Generative models with kernel distance in data space
Generative models dealing with modeling a joint data distribution are ge...
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Adversarial Examples Detection and Analysis with Layerwise Autoencoders
We present a mechanism for detecting adversarial examples based on data ...
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HyperFlow: Representing 3D Objects as Surfaces
In this work, we present HyperFlow  a novel generative model that lever...
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LocoGAN – Locally Convolutional GAN
In the paper we construct a fully convolutional GAN model: LocoGAN, whic...
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WICA: nonlinear weighted ICA
Independent Component Analysis (ICA) aims to find a coordinate system in...
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Geometric Graph Convolutional Neural Networks
Graph Convolutional Networks (GCNs) have recently become the primary cho...
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Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models
We present an efficient technique, which allows to train classification ...
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Independent Component Analysis based on multiple dataweighting
Independent Component Analysis (ICA)  one of the basic tools in data an...
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Oneelement Batch Training by Moving Window
Several deep models, esp. the generative, compare the samples from two d...
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Nonlinear ICA based on CramerWold metric
Nonlinear source separation is a challenging open problem with many app...
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Sliced generative models
In this paper we discuss a class of AutoEncoder based generative models ...
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Deep processing of structured data
We construct a general unified framework for learning representation of ...
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CramerWold AutoEncoder
We propose a new generative model, CramerWold Autoencoder (CWAE). Follo...
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Processing of missing data by neural networks
We propose a general, theoretically justified mechanism for processing m...
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Introduction to CrossEntropy Clustering The R Package CEC
The R Package CEC performs clustering based on the crossentropy cluster...
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Przemysław Spurek
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