matwilso / maml_numpyLinks
Implementation of MAML in numpy, deriving gradients and implementing backprop manually
☆14Updated 7 years ago
Alternatives and similar repositories for maml_numpy
Users that are interested in maml_numpy are comparing it to the libraries listed below
Sorting:
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- This is the official source code for Sequential Neural Processes.☆40Updated 3 years ago
- PyTorch implementation of "STNs" and "Delta-STNs".☆50Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 5 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Implementation of: Kristiadi, Agustinus, and Asja Fischer. "Predictive Uncertainty Quantification with Compound Density Networks." (2019)…☆16Updated 3 years ago
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆21Updated 2 years ago
- Official Code Repository for La-MAML: Look-Ahead Meta-Learning for Continual Learning"☆79Updated 5 years ago
- Package for working with hypernetworks in PyTorch.☆131Updated 2 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 5 years ago
- Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding☆73Updated 4 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆101Updated 7 years ago
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- ☆54Updated last year
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆35Updated 4 years ago
- Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning☆102Updated 4 years ago
- A minimal pytorch implementation of VAE, IWAE, MIWAE☆47Updated 3 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆76Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 5 years ago
- ☆105Updated 4 years ago
- Pytorch implementation of Neural Processes for functions and images☆236Updated 3 years ago
- Code for "MetaFun: Meta-Learning with Iterative Functional Updates"☆14Updated 5 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆90Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Implementation of the Convolutional Conditional Neural Process☆128Updated 4 years ago