wendazhou / nnet-compression-generalization
☆27Updated 6 years ago
Alternatives and similar repositories for nnet-compression-generalization:
Users that are interested in nnet-compression-generalization are comparing it to the libraries listed below
- 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
- This repository is no longer maintained. Check☆81Updated 4 years ago
- Lua implementation of Entropy-SGD☆81Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- ☆13Updated 6 years ago
- ☆26Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch☆62Updated 4 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated last month
- code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning☆26Updated 6 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning☆23Updated 6 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for paper "Convergent Learning: Do different neural networks learn the same representations?"☆86Updated 8 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- ☆34Updated 6 years ago
- ☆45Updated 5 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- ☆36Updated 3 years ago
- Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."☆34Updated 6 years ago
- ☆46Updated 7 years ago
- The Singular Values of Convolutional Layers☆72Updated 6 years ago
- Code for "Adversarial Distillation of Bayesian Neural Network Posteriors" https://arxiv.org/abs/1806.10317☆15Updated 6 years ago
- Net2Net implementation on PyTorch for any possible vision layers.☆38Updated 7 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated last year