Posts about mathjax
- Bayesian Learning via Stochastic Gradient Langevin Dynamics and Bayes by Backprop
- An Introduction to Stochastic Calculus
- Normalizing Flows with Real NVP
- Hamiltonian Monte Carlo
- Lossless Compression with Latent Variable Models using Bits-Back Coding
- Lossless Compression with Asymmetric Numeral Systems
- Model Explainability with SHapley Additive exPlanations (SHAP)
- A Note on Using Log-Likelihood for Generative Models
- PixelCNN
- Importance Sampling and Estimating Marginal Likelihood in Variational Autoencoders
- Label Refinery: A Softer Approach
- Universal ResNet: The One-Neuron Approximator
- Hyperbolic Geometry and Poincaré Embeddings
- Manifolds: A Gentle Introduction
- Tensors, Tensors, Tensors
- Residual Networks
- Variational Autoencoders with Inverse Autoregressive Flows
- Autoregressive Autoencoders
- Semi-supervised Learning with Variational Autoencoders
- A Variational Autoencoder on the SVHN dataset
- Variational Autoencoders
- Variational Bayes and The Mean-Field Approximation
- The Calculus of Variations
- Maximum Entropy Distributions
- Lagrange Multipliers
- The Expectation-Maximization Algorithm
- A Probabilistic Interpretation of Regularization
- A Probabilistic View of Linear Regression
- Elementary Statistics for Direct Marketing
- A Primer on Statistical Inference and Hypothesis Testing
- Optimal Betting Strategies and The Kelly Criterion
- Probability as Extended Logic
- Accessible Satisfiability