Data Visualization

43 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Adversarial Autoencoders

eriklindernoren/PyTorch-GAN 18 Nov 2015

In this paper, we propose the "adversarial autoencoder" (AAE), which is a probabilistic autoencoder that uses the recently proposed generative adversarial networks (GAN) to perform variational inference by matching the aggregated posterior of the hidden code vector of the autoencoder with an arbitrary prior distribution.

ShapeNet: An Information-Rich 3D Model Repository

tensorflow/models 9 Dec 2015

We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects.

A high-bias, low-variance introduction to Machine Learning for physicists

drckf/mlreview_notebooks 23 Mar 2018

The purpose of this review is to provide an introduction to the core concepts and tools of machine learning in a manner easily understood and intuitive to physicists.

Data2Vis: Automatic Generation of Data Visualizations Using Sequence to Sequence Recurrent Neural Networks

victordibia/data2vis 9 Apr 2018

Rapidly creating effective visualizations using expressive grammars is challenging for users who have limited time and limited skills in statistics and data visualization.

A new robust feature selection method using variance-based sensitivity analysis

5amron/feature_selection_using_sensitivity_analysis 13 Apr 2018

Excluding irrelevant features in a pattern recognition task plays an important role in maintaining a simpler machine learning model and optimizing the computational efficiency.

Torchbearer: A Model Fitting Library for PyTorch

ecs-vlc/torchbearer 10 Sep 2018

We introduce torchbearer, a model fitting library for pytorch aimed at researchers working on deep learning or differentiable programming.

Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment

gitr00ki3/vpw 7 Dec 2002

Nonlinear manifold learning from unorganized data points is a very challenging unsupervised learning and data visualization problem with a great variety of applications.

Doubly Stochastic Neighbor Embedding on Spheres

yaolubrain/DOSNES 7 Sep 2016

To solve this problem, we introduce a fast normalization method and normalize the similarity matrix to be doubly stochastic such that all the data points have equal total similarities.

VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution

uber-common/deep-neuroevolution 3 May 2018

Recent advances in deep neuroevolution have demonstrated that evolutionary algorithms, such as evolution strategies (ES) and genetic algorithms (GA), can scale to train deep neural networks to solve difficult reinforcement learning (RL) problems.

Kernelized Synaptic Weight Matrices

lorenzMuller/kernelNet_MovieLens ICML 2018

In this paper we introduce a novel neural network architecture, in which weight matrices are re-parametrized in terms of low-dimensional vectors, interacting through kernel functions.