Links to some important research papers or links. I plan to add notes as I go through each topic one by one.
- Invariant Information Clustering
- Mutual Information Neural Estimation
- Deep Infomax
- Learning Representations by Maximizing Mutual Information Across Views
- How Google decoupled MI maximization and representation learning: On Mutual Information Maximization for Representation Learning
- Quick overview by Google
- β-VAE, pdf
- Understanding disentangling in β-VAE
- Disentangling Disentanglement in Variational Autoencoders
- Isolating Sources of Disentanglement in Variational Autoencoders
- InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers
- Disentangling by Factorising, pdf
- Representation Learning with Contrastive Predictive Coding
- Data-Efficient Image Recognition with Contrastive Predictive Coding
- Contrastive Multiview Coding
- Momentum Contrast for Unsupervised Visual Representation Learning
- Google disspelling a lot of misconceptions about disentangled representations: Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
- Automatic differentiation in machine learning: a survey
- Automatic Reverse-Mode Differentiation: Lecture Notes
- Reverse mode automatic differentiation
- Neural Ordinary Differential Equations
- Augmented Neural ODEs
- Invertible ResNets
- Universal Differential Equations for Scientific Machine Learning
- Probabilistic models of cognition
- The Design and Implementation of Probabilistic Programming Languages
- Composition in Probabilistic Language Understanding
- Detailed hands-on introduction
- Normalizing Flows for Probabilistic Modeling and Inference
- PyTorch implementations of density estimation algorithms
- Zero-shot knowledge transfer
- SpecNet
- Deep Learning & Symbolic Mathematics
- Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
- Deep Equilibrium Models
- Lottery ticket hypothesis
- Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
- Rigging the Lottery: Making All Tickets Winners
- What's Hidden in a Randomly Weighted Neural Network?
- Topological properties of the set of functions generated by neural networks of fixed size
- YOUR CLASSIFIER IS SECRETLY AN ENERGY BASED MODEL AND YOU SHOULD TREAT IT LIKE ONE
- Amortized Population Gibbs Samplers with Neural Sufficient Statistics
- Evaluating Combinatorial Generalization in Variational Autoencoders