Deep Learning with Machine Learning

Published: 09 Oct 2015 Category: deep_learning


Scalable Bayesian Optimization Using Deep Neural Networks

Bayesian Dark Knowledge

Memory-based Bayesian Reasoning with Deep Learning

Towards Bayesian Deep Learning: A Survey

Towards Bayesian Deep Learning: A Framework and Some Existing Methods

Bayesian Deep Learning: Neural Networks in PyMC3 estimated with Variational Inference

Bayesian Deep Learning Part II: Bridging PyMC3 and Lasagne to build a Hierarchical Neural Network

Deep Bayesian Active Learning with Image Data

Deep Learning: A Bayesian Perspective

On Bayesian Deep Learning and Deep Bayesian Learning

Bayesian Neural Networks

Bayesian Convolutional Neural Networks

Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam

Bag of Words (BoW)

Deep Learning Transcends the Bag of Words

E2BoWs: An End-to-End Bag-of-Words Model via Deep Convolutional Neural Network


Deep Boosting

Deep Incremental Boosting


Training Deep Neural Networks on Noisy Labels with Bootstrapping

ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning

Compressive Sensing

ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning

Perceptual Compressive Sensing

Full Image Recover for Block-Based Compressive Sensing

Conditional Random Fields

Deep Markov Random Field for Image Modeling

Deep, Dense, and Low-Rank Gaussian Conditional Random Fields

DeepCRF: Neural Networks and CRFs for Sequence Labeling

Decision Tree

Deep Neural Decision Forests

Neural Network and Decision Tree

Decision Forests, Convolutional Networks and the Models in-Between

Distilling a Neural Network Into a Soft Decision Tree

End-to-end Learning of Deterministic Decision Trees

Deep Neural Decision Trees

Adaptive Neural Trees

Visualizing the decision-making process in deep neural decision forest

NBDT: Neural-Backed Decision Trees

Dictionary Learning

Greedy Deep Dictionary Learning

Sparse Factorization Layers for Neural Networks with Limited Supervision

Online Convolutional Dictionary Learning

Deep Dictionary Learning: A PARametric NETwork Approach

Deep Micro-Dictionary Learning and Coding Network

Fisher Vectors

Backpropagation Training for Fisher Vectors within Neural Networks

Semi-supervised Fisher vector network

Gaussian Processes

Questions on Deep Gaussian Processes

Qs – Deep Gaussian Processes

Practical Learning of Deep Gaussian Processes via Random Fourier Features

Deep Learning with Gaussian Process

Doubly Stochastic Variational Inference for Deep Gaussian Processes

Deep Gaussian Mixture Models

How Deep Are Deep Gaussian Processes?

Variational inference for deep Gaussian processes

Deep Gaussian Processes with Decoupled Inducing Inputs

Gaussian Process Behaviour in Wide Deep Neural Networks

Differentiable Compositional Kernel Learning for Gaussian Processes

Deep Convolutional Networks as shallow Gaussian Processes

Deep convolutional Gaussian processes

Graph Convolutional Gaussian Processes

Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes

Graphical Models

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models


DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model


Unsupervised Neural Hidden Markov Models


Learnable Histogram: Statistical Context Features for Deep Neural Networks

Kalman Filter

Deep Robust Kalman Filter

Kernel Methods

Kernel Methods for Deep Learning

Deep Kernel Learning

Stochastic Variational Deep Kernel Learning

A Deep Learning Approach To Multiple Kernel Fusion

Optimizing Kernel Machines using Deep Learning

Stacked Kernel Network

Deep Embedding Kernel

Learning Explicit Deep Representations from Deep Kernel Networks

k-Nearest Neighbors

Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning


Deep Local Binary Patterns

Local Binary Pattern Networks

Neural Nearest Neighbors Networks

Deep Logistic Regression

Single-Label Multi-Class Image Classification by Deep Logistic Regression

Probabilistic Programming

Deep Probabilistic Programming with Edward


Large-scale Learning with SVM and Convolutional for Generic Object Categorization

Convolutional Neural Support Vector Machines:Hybrid Visual Pattern Classifiers for Multi-robot Systems

Deep Learning using Linear Support Vector Machines

Deep Support Vector Machines

Random Forest

Towards the effectiveness of Deep Convolutional Neural Network based Fast Random Forest Classifier

Deep Forest: Towards An Alternative to Deep Neural Networks

Forward Thinking: Building Deep Random Forests

Deep Regression Forests for Age Estimation

Deep Differentiable Random Forests for Age Estimation

Template Matching

QATM: Quality-Aware Template Matching For Deep Learning