wangkua1 / apd_public
Code for "Adversarial Distillation of Bayesian Neural Network Posteriors" https://arxiv.org/abs/1806.10317
☆15Updated 6 years ago
Alternatives and similar repositories for apd_public:
Users that are interested in apd_public are comparing it to the libraries listed below
- ☆13Updated 6 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆34Updated 7 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆60Updated 6 years ago
- ☆53Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆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
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Lua implementation of Entropy-SGD☆81Updated 6 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- Implementation of Information Dropout☆39Updated 7 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
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- Tensorflow implementation of DropMax: Adaptive Variational Softmax (NeurIPS2018)☆18Updated 4 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated last year
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- ☆63Updated 8 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆35Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- The Deep Weight Prior, ICLR 2019☆44Updated 3 years ago
- code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning☆26Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 5 months ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago