felix-laumann / Bayesian_CNN_ContinualLearningLinks
Interpreting Bayesian inference as continual learning with a CNN
☆22Updated 7 years ago
Alternatives and similar repositories for Bayesian_CNN_ContinualLearning
Users that are interested in Bayesian_CNN_ContinualLearning are comparing it to the libraries listed below
Sorting:
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf☆30Updated 5 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆114Updated 4 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆138Updated 7 years ago
- Implementation of the variational continual learning method☆192Updated 6 years ago
- ☆237Updated 5 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆66Updated 2 years ago
- ☆10Updated 6 years ago
- ☆16Updated 7 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Extreme Learning Machine implemented in Pytorch☆103Updated 7 years ago
- ☆46Updated 2 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 7 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆75Updated 4 years ago
- Implementation of Bayesian Gradient Descent☆37Updated last year
- Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015☆36Updated 7 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆45Updated 4 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆103Updated 5 years ago
- Pytorch implementation of Adaptative Dropout a.ka Standout.☆12Updated 7 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- PyTorch implementation of Stacked Capsule Auto-Encoders☆39Updated last year
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- Codebase for "Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning". This is a ServiceNow Research pro…☆105Updated 3 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆93Updated 7 years ago
- Master Thesis on Bayesian Convolutional Neural Network using Variational Inference☆264Updated 6 years ago
- Dropout as Regularization and Bayesian Approximation☆59Updated 6 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- ☆26Updated 6 years ago