ucla-vision / information-dropout
Implementation of Information Dropout
☆39Updated 7 years ago
Alternatives and similar repositories for information-dropout:
Users that are interested in information-dropout are comparing it to the libraries listed below
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 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
- ☆13Updated 6 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- The Deep Weight Prior, ICLR 2019☆45Updated 4 years ago
- Echo Noise Channel for Exact Mutual Information Calculation☆17Updated 4 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- Lua implementation of Entropy-SGD☆82Updated 7 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning☆23Updated 6 years ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated 2 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 6 years ago
- Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W Ding · Y.C. Lui · …☆20Updated 6 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆35Updated 4 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- ☆26Updated 6 years ago
- rich posterior approximations and anomaly detection☆20Updated 6 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago