g-benton / learning-invariancesLinks
Codebase for Learning Invariances in Neural Networks
☆96Updated 2 years ago
Alternatives and similar repositories for learning-invariances
Users that are interested in learning-invariances are comparing it to the libraries listed below
Sorting:
- ☆54Updated last year
- 🧀 Pytorch code for the Fromage optimiser.☆128Updated last year
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- ☆100Updated 3 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆57Updated 4 years ago
- ☆64Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- Monotone operator equilibrium networks☆53Updated 5 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆41Updated 4 years ago
- Last-layer Laplace approximation code examples☆84Updated 3 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 3 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated 2 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆147Updated 2 years ago
- Hypergradient descent☆149Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated 2 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆80Updated 3 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation☆67Updated 3 years ago
- A Machine Learning workflow for Slurm.☆151Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆84Updated 2 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆54Updated 2 years ago
- Padé Activation Units: End-to-end Learning of Activation Functions in Deep Neural Network☆63Updated 4 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge☆62Updated 2 years ago
- Drop-in replacement for any ResNet with a significantly reduced memory footprint and better representation capabilities☆208Updated last year
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago