jinxu06 / metafun-tensorflowLinks
Code for "MetaFun: Meta-Learning with Iterative Functional Updates"
☆14Updated 4 years ago
Alternatives and similar repositories for metafun-tensorflow
Users that are interested in metafun-tensorflow are comparing it to the libraries listed below
Sorting:
- Functional Regularisation for Continual Learning with Gaussian Processes☆14Updated 4 years ago
- code for Stein Neural Sampler☆22Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 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 the Functional Neural Process models☆43Updated 4 years ago
- Library for Auto-Encoding Sequential Monte Carlo☆18Updated last year
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching☆12Updated 2 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Code for paper "Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow"☆19Updated 4 years ago
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆21Updated 2 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A PyTorch Implementation of the Importance Weighted Autoencoders☆40Updated 6 years ago
- ☆28Updated 3 years ago
- ☆53Updated 10 months ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- ☆64Updated last year
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 7 months ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated 2 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆45Updated last year
- Monotone operator equilibrium networks☆52Updated 4 years ago
- Implicit Generation and Generalization in Energy Based Models in PyTorch☆65Updated 6 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago