AWehenkel / generalized-UMNN
Extension to multivariate unconstrained monotonic functions.
☆12Updated 5 years ago
Alternatives and similar repositories for generalized-UMNN:
Users that are interested in generalized-UMNN are comparing it to the libraries listed below
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆118Updated 3 months ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last year
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago
- ☆53Updated 8 months ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 5 months ago
- Python implementation of smooth optimal transport.☆57Updated 3 years ago
- ☆15Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 4 years ago
- ☆38Updated 4 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Convolutional Neural Tangent Kernel☆109Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆37Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Difference-of-Entropies (DoE) Estimator☆25Updated 2 years ago