bneyshabur / over-parametrization
Computing various norms/measures on over-parametrized neural networks
☆49Updated 6 years ago
Alternatives and similar repositories for over-parametrization:
Users that are interested in over-parametrization are comparing it to the libraries listed below
- 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
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- ☆13Updated 6 years ago
- ☆26Updated 5 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Lua implementation of Entropy-SGD☆81Updated 6 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆48Updated 5 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning☆23Updated 6 years ago
- Implementation of REBAR in PyTorch☆17Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 6 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆35Updated 4 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 6 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆63Updated 4 years ago
- ☆34Updated 6 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆34Updated 7 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆67Updated 5 years ago
- This repository is no longer maintained. Check☆81Updated 4 years ago