neale / HyperGAN
Generative Model for Neural Networks
☆24Updated 4 years ago
Alternatives and similar repositories for HyperGAN:
Users that are interested in HyperGAN are comparing it to the libraries listed below
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Code for Unsupervised Learning via Meta-Learning.☆65Updated 4 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 6 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆35Updated 4 years ago
- ☆13Updated 6 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- ☆36Updated 3 years ago
- ☆89Updated 3 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 5 years ago
- Hyper volume maximization for GAN training☆25Updated 5 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆26Updated 3 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 5 years ago
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆21Updated 2 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆55Updated 3 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Implementation of Bayesian Gradient Descent☆37Updated last year
- Coresets via Bilevel Optimization☆65Updated 4 years ago
- Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."☆34Updated 6 years ago
- ☆46Updated 2 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- (NeurIPS 2020) Meta-Consolidation for Continual Learning☆36Updated 4 years ago
- Automatic Recall Machines: Internal Replay, Continual Learning and the Brain☆11Updated 4 years ago
- Official Implementation of "Random Path Selection for Incremental Learning" paper. NeurIPS 2019☆53Updated 2 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆34Updated 7 years ago
- ☆21Updated 2 years ago
- ☆53Updated 5 years ago