joelouismarino / iterative_inferenceLinks
Implementation of iterative inference in deep latent variable models
☆43Updated 5 years ago
Alternatives and similar repositories for iterative_inference
Users that are interested in iterative_inference are comparing it to the libraries listed below
Sorting:
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated 2 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"☆121Updated 6 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- ☆37Updated 5 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 6 years ago
- Measuring compositionality in representation learning☆73Updated 6 years ago
- Implementation of REBAR in PyTorch☆17Updated 6 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- ☆26Updated 6 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Lagrangian VAE☆28Updated 6 years ago
- Like Moving MNIST, but way more flexible☆24Updated 4 years ago
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆52Updated 7 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago