Academic Paper Bookmark

This blog intends to bookmark the academic papers in the field of computer science–mainly machine learning–that I plan to or have already read (continuing)

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• Variational Inference with Normalizing Flows

• A family of non-parametric density estimation algorithms

• Masked Autoregressive Flow for Density Estimation

• MADE: Masked Autoencoder for Distribution Estimation

• Pixel Recurrent Neural Networks

• Masked Autoregressive Flow for Density Estimation

• Auto-Encoding Variational Bayes

• Stochastic Backpropagation and Approximate Inference in Deep Generative Models

• The Neural Autoregressive Distribution Estimator

• ImageNet Classification with Deep Convolutional Neural Networks

• Going deeper with convolutions

• Deep Residual Learning for Image Recognition

• Variational Inference with Normalizing Flows

• Sylvester Normalizing Flows for Variational Inference

• Learnable Explicit Density for Continuous Latent Space and Variational Inference

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting

• ImageNet Classification with Deep Convolutional Neural Networks

• Improving Neural Networks with Dropout

• ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION

• On the momentum term in gradient descent learning algorithms

• An overview of gradient descent optimization algorithms