Skip to content

Latest commit

 

History

History
452 lines (271 loc) · 19.5 KB

2015-10-09-unsupervised-learning.md

File metadata and controls

452 lines (271 loc) · 19.5 KB
Raw
layout category title date
post
deep_learning
Unsupervised Learning
2015-10-09

Restricted Boltzmann Machine (RBM)

Sparse Coding

Fast Convolutional Sparse Coding in the Dual Domain

https://arxiv.org/abs/1709.09479

Auto-encoder

Papers

On Random Weights and Unsupervised Feature Learning

Unsupervised Learning of Spatiotemporally Coherent Metrics

Unsupervised Learning of Visual Representations using Videos

Unsupervised Visual Representation Learning by Context Prediction

Unsupervised Learning on Neural Network Outputs

Unsupervised Domain Adaptation by Backpropagation

Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

Tagger: Deep Unsupervised Perceptual Grouping

Regularization for Unsupervised Deep Neural Nets

Sparse coding: A simple exploration

Navigating the unsupervised learning landscape

Unsupervised Learning using Adversarial Networks

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction

Learning Features by Watching Objects Move

CNN features are also great at unsupervised classification

Supervised Convolutional Sparse Coding

https://arxiv.org/abs/1804.02678

Momentum Contrast for Unsupervised Visual Representation Learning

Improved Baselines with Momentum Contrastive Learning

Clustering

Deep clustering: Discriminative embeddings for segmentation and separation

Neural network-based clustering using pairwise constraints

Unsupervised Deep Embedding for Clustering Analysis

Joint Unsupervised Learning of Deep Representations and Image Clusters

Single-Channel Multi-Speaker Separation using Deep Clustering

Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering

Deep Unsupervised Clustering with Gaussian Mixture Variational

Variational Deep Embedding: A Generative Approach to Clustering

A new look at clustering through the lens of deep convolutional neural networks

Deep Subspace Clustering Networks

SpectralNet: Spectral Clustering using Deep Neural Networks

Clustering with Deep Learning: Taxonomy and New Methods

Deep Continuous Clustering

Learning to Cluster

Learning Neural Models for End-to-End Clustering

Deep Clustering for Unsupervised Learning of Visual Features

Improving Image Clustering With Multiple Pretrained CNN Feature Extractors

Deep clustering: On the link between discriminative models and K-means

https://arxiv.org/abs/1810.04246

Deep Density-based Image Clustering

https://arxiv.org/abs/1812.04287

Deep Representation Learning Characterized by Inter-class Separation for Image Clustering

Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding

Contrastive Clustering

https://arxiv.org/abs/2009.09687

Deep Clustering by Semantic Contrastive Learning

Auto-encoder

Auto-Encoding Variational Bayes

The Potential Energy of an Autoencoder

Importance Weighted Autoencoders

Review of Auto-Encoders

Stacked What-Where Auto-encoders

Ladder Variational Autoencoders

How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks

Rank Ordered Autoencoders

Decoding Stacked Denoising Autoencoders

Keras autoencoders (convolutional/fcc)

Building Autoencoders in Keras

Review of auto-encoders

Autoencoders: Torch implementations of various types of autoencoders

Tutorial on Variational Autoencoders

Variational Autoencoders Explained

Introducing Variational Autoencoders (in Prose and Code)

Under the Hood of the Variational Autoencoder (in Prose and Code)

The Unreasonable Confusion of Variational Autoencoders

Variational Autoencoder for Deep Learning of Images, Labels and Captions

Convolutional variational autoencoder with PyMC3 and Keras

http://nbviewer.jupyter.org/github/taku-y/pymc3/blob/89b8634a2fd30ef96429953558bf360132b6153f/docs/source/notebooks/convolutional_vae_keras_advi.ipynb

Pixelvae: A Latent Variable Model For Natural Images

beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework

Variational Lossy Autoencoder

Convolutional Autoencoders

Convolutional Autoencoders in Tensorflow

A Deep Convolutional Auto-Encoder with Pooling - Unpooling Layers in Caffe

Deep Matching Autoencoders

Understanding Autoencoders with Information Theoretic Concepts

Hyperspherical Variational Auto-Encoders

Spatial Frequency Loss for Learning Convolutional Autoencoders

https://arxiv.org/abs/1806.02336

DAQN: Deep Auto-encoder and Q-Network

https://arxiv.org/abs/1806.00630

Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer

RBM (Restricted Boltzmann Machine)

Papers

Deep Boltzmann Machines

On the Equivalence of Restricted Boltzmann Machines and Tensor Network States

Matrix Product Operator Restricted Boltzmann Machines

https://arxiv.org/abs/1811.04608

Blogs

A Tutorial on Restricted Boltzmann Machines

http://xiangjiang.live/2016/02/12/a-tutorial-on-restricted-boltzmann-machines/

Dreaming of names with RBMs

on Cheap Learning: Partition Functions and RBMs

Improving RBMs with physical chemistry

Projects

Restricted Boltzmann Machine (Haskell)

tensorflow-rbm: Tensorflow implementation of Restricted Boltzman Machine

Videos

Modelling a text corpus using Deep Boltzmann Machines

Foundations of Unsupervised Deep Learning