prolearner / hyper-representationLinks
This is the official repo for the experiments in the paper "Bilevel Programming for Hyperparameter Optimization and Meta-Learning"
☆29Updated 7 years ago
Alternatives and similar repositories for hyper-representation
Users that are interested in hyper-representation are comparing it to the libraries listed below
Sorting:
- ☆123Updated last year
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 7 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Sliced Wasserstein Generator☆38Updated 7 years ago
- ☆17Updated 3 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 4 years ago
- Code for Invariant Rep. Without Adversaries (NIPS 2018)☆35Updated 5 years ago
- Library to manage machine learning problems as `Tasks' and to sample from Task distributions. Includes Tensorflow implementation of impli…☆48Updated 3 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- A collection of Gradient-Based Meta-Learning Algorithms with pytorch☆62Updated 5 years ago
- CFG-GAN: Composite functional gradient learning of generative adversarial models☆15Updated 4 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching☆27Updated 6 years ago
- ☆91Updated 3 years ago
- Generative Model for Neural Networks☆24Updated 4 years ago
- ☆58Updated 2 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 8 months ago
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- "Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.☆60Updated 5 years ago
- ☆46Updated 7 years ago
- ☆20Updated 5 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 6 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- ☆32Updated 6 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Scaleable input gradient regularization☆22Updated 5 years ago
- Generator loss to reduce mode-collapse and to improve the generated samples quality.☆34Updated 5 years ago
- Gradient based hyperparameter optimization & meta-learning package for TensorFlow☆188Updated 5 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 5 years ago