greentfrapp / cond-shift-neuronsLinks
Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)
☆28Updated 6 years ago
Alternatives and similar repositories for cond-shift-neurons
Users that are interested in cond-shift-neurons are comparing it to the libraries listed below
Sorting:
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Code for "Systematic Generalization: What Is Required and Can It Be Learned"☆37Updated 6 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- Experiments from "The Description Length of Deep Learning Models"☆10Updated 6 years ago
- ☆26Updated 6 years ago
- ZForcing Repo☆40Updated 7 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- boundary-seeking generative adversarial networks☆46Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Implementation of "Learning with Random Learning Rates" in PyTorch.☆102Updated 5 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆48Updated 7 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Repository of code for the experiments for the ICLR submission "An Empirical Investigation of Catastrophic Forgetting in Gradient-Based N…☆68Updated 11 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for the paper "Learning sparse transformations through backpropagation"☆43Updated 5 years ago
- Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"☆121Updated 6 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- Deep variational inference in tensorflow☆56Updated 7 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch☆57Updated 7 years ago
- ☆61Updated 2 years ago
- PyTorch implementation of PathNet: Evolution Channels Gradient Descent in Super Neural Networks☆80Updated 7 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago
- ☆63Updated 8 years ago
- PyTorch code for meta seq2seq learning☆43Updated 5 years ago
- Implementation of Adversarial Variational Optimization in PyTorch☆43Updated 6 years ago
- Implementation of Coulomb GANs☆62Updated 3 years ago
- An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…☆72Updated 7 years ago