maartjeth / sacred-example-pytorch
Some example code that shows you how to use Sacred in a full Pytorch project.
☆28Updated 4 years ago
Alternatives and similar repositories for sacred-example-pytorch:
Users that are interested in sacred-example-pytorch are comparing it to the libraries listed below
- A collection of code snippets for my PyTorch Lightning projects☆107Updated 4 years ago
- Drop-in replacement for any ResNet with a significantly reduced memory footprint and better representation capabilities☆209Updated 11 months ago
- [NeurIPS 2019] Deep Set Prediction Networks☆100Updated 4 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆79Updated 3 years ago
- Codebase for Learning Invariances in Neural Networks☆94Updated 2 years ago
- CPAB Transformations: finite-dimensional spaces of simple, fast, and highly-expressive diffeomorphisms derived from parametric, continuou…☆48Updated 3 years ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆83Updated 3 years ago
- Python implementation of GLN in different frameworks☆98Updated 4 years ago
- Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder☆161Updated 4 years ago
- On disentangling the menagerie of disentanglement papers☆27Updated 5 years ago
- This repository contains the results for the paper: "Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers"☆180Updated 3 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…☆40Updated 4 years ago
- Implementation of the Convolutional Conditional Neural Process☆120Updated 3 years ago
- Code repository for the paper "Attentive Group Equivariant Convolutional Neural Networks" published at ICML 2020. https://arxiv.org/abs/2…☆50Updated 4 years ago
- A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.☆125Updated last year
- ☆240Updated 2 years ago
- Pytorch implementation of Neural Processes for functions and images☆227Updated 3 years ago
- Semantic Segmentation with Pytorch-Lightning☆63Updated 4 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆145Updated last year
- A Pytorch Implementation of Attentive Neural Process☆72Updated 5 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- Official code for the Stochastic Polyak step-size optimizer☆139Updated 9 months ago
- Notes and codes of the topic "Bayesian deep learning"☆56Updated 6 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆123Updated 8 months ago
- Torchélie is a set of utility functions, layers, losses, models, trainers and other things for PyTorch.☆110Updated 3 months ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Prescribed Generative Adversarial Networks☆143Updated 4 years ago
- [NeurIPS'20] Multiscale Deep Equilibrium Models☆233Updated 3 years ago
- Implements stochastic line search☆118Updated 2 years ago
- Pytorch implementation of the hamburger module from the ICLR 2021 paper "Is Attention Better Than Matrix Decomposition"☆98Updated 4 years ago