g-benton / learning-invariances
Codebase for Learning Invariances in Neural Networks
☆93Updated 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
- ☆98Updated 3 years ago
- ☆53Updated 6 months ago
- Last-layer Laplace approximation code examples☆83Updated 3 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆123Updated 7 months ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 3 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 9 months ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆65Updated 10 months ago
- A library for evaluating representations.☆74Updated 3 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆40Updated 2 years ago
- A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.☆125Updated last year
- ☆34Updated 3 years ago
- ☆33Updated 4 years ago
- ☆63Updated last year
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated last year
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆145Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Geometric Certifications of Neural Nets☆41Updated 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, …☆111Updated 6 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆78Updated 2 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆83Updated 2 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 2 years ago
- Hessian spectral density estimation in TF and Jax☆121Updated 4 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago