A list of useful resources and paper
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  • Identifying and attacking the saddle point problem in high-dimensional non-convex optimization


  • Implicit Reparameterization Gradients

Interpretable Models

  • Measuring the Intrinsic Dimension of Objective Landscapes
  • Insights on representational similarity in neural networks with canonical correlation

Variational Methods

  • Variational Inference and Deep Learning: A New Synthesis
  • Auto-Encoding Variational Bayes
  • An Introduction to Variational Methods for Graphical Models

Discrete Latent Space

  • Neural Discrete Representation Learning
  • The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
  • Categorical Reparameterization with Gumbel-Softmax

Policy Gradients

  • Trust Region Policy Optimization
  • Proximal Policy Optimization Algorithms
  • Deterministic Policy Gradient Algorithms
  • Continuous control with deep reinforcement learning

Actor Critic

  • Asynchronous Methods for Deep Reinforcement Learning
  • High-Dimensional Continuous Control Using Generalized Advantage Estimation


  • Human-level control through deep reinforcement learning
  • Deep Reinforcement Learning with Double Q-learning

Energy Models

  • A Tutorial on Energy-Based Learning
  • An Introduction to Restricted Boltzmann Machines

Markov Models

  • A tutorial on hidden Markov models and selected applications in speech recognition

Program Synthesis

  • Supervised Sequence Labelling with Recurrent Neural Networks

Sequential Models

  • Supervised Sequence Labelling with Recurrent Neural Networks


  • AllenNLP
  • Semantics
  • spaCy
  • Wit.ai extracting named entities
  • Duckling parses text into structured data.