64 papers with code • 0 benchmarks • 1 datasets
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Most implemented papers
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
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
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
Rapidly creating effective visualizations using expressive grammars is challenging for users who have limited time and limited skills in statistics and data visualization.
Kernelized Synaptic Weight Matrices
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.
Torchbearer: A Model Fitting Library for PyTorch
We introduce torchbearer, a model fitting library for pytorch aimed at researchers working on deep learning or differentiable programming.
Detectron2 Object Detection & Manipulating Images using Cartoonization
In today's world, there is a rapid increase in the autonomous vehicle.
Geometry- and Accuracy-Preserving Random Forest Proximities
Random forests are considered one of the best out-of-the-box classification and regression algorithms due to their high level of predictive performance with relatively little tuning.
Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment
Nonlinear manifold learning from unorganized data points is a very challenging unsupervised learning and data visualization problem with a great variety of applications.