# Posts for year 2017

- A Simple Illustration of Density Ratio Estimation and KL Divergence Estimation by Probabilistic Classification
- Calculating KL divergence in closed-form versus Monte Carlo estimation
- Bayesian Sparse Logistic Regression with Spike-and-Slab Priors (using Edward)
- Alternative definition of logistic regression model as multi-input and multi-output model in Keras
- Difference between Keras stack and concatenate
- Using negative log-likelihoods of TensorFlow Distributions as Keras losses
- A Probabilistic Interpretation of CycleGAN as Approximate Bayesian Inference with Implicit Distributions
- Inference in Variational Autoencoders with Different Monte Carlo Sample Sizes (Addendum)
- Inference in Variational Autoencoders with Different Monte Carlo Sample Sizes
- Keras Constant Input Layers with Fixed Source of Stochasticity
- Working with Pandas MultiIndex Dataframes: Reading and Writing to CSV and HDF5
- Implementing Variational Autoencoders in Keras: Beyond the Quickstart Tutorial
- Working with Samples of Distributions over Convolutional Kernels
- Variational Inference with Implicit Approximate Inference Models - @fhuszar's Explaining Away Example Pt. 1 (WIP)
- Variational Inference with Implicit Approximate Inference Models (WIP Pt. 9)
- Variational Inference with Implicit Approximate Inference Models (WIP Pt. 8)
- Variational Inference with Implicit Models (forked from @fhuszar)
- My PhD in Weeks
- Visualizing the Latent Space of Vector Drawings from the Google QuickDraw Dataset with SketchRNN, PCA and t-SNE
- Exploring the Google QuickDraw Dataset with SketchRNN (Part 3)
- Exploring the Google QuickDraw Dataset with SketchRNN (Part 2)
- Exploring the Google QuickDraw Dataset with SketchRNN (Part 1)
- Trigonometric functions with recursion and higher-order functions in Python