AWehenkel / UMNNLinks
Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for modelling monotonic transformations in normalizing flows.
☆120Updated 6 months ago
Alternatives and similar repositories for UMNN
Users that are interested in UMNN are comparing it to the libraries listed below
Sorting:
- Masked Autoregressive Flow☆213Updated 11 months ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆101Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- ☆24Updated 3 years ago
- Deep neural network kernel for Gaussian process☆208Updated 4 years ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- Discrete Normalizing Flows implemented in PyTorch☆114Updated 3 years ago
- Extension to multivariate unconstrained monotonic functions.☆12Updated 5 years ago
- Manifold-learning flows (ℳ-flows)☆230Updated 4 years ago
- Random Fourier Features☆49Updated 8 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Official repository for "Categorical Normalizing Flows via Continuous Transformations"☆56Updated 4 years ago
- Real NVP PyTorch a Minimal Working Example | Normalizing Flow☆139Updated 4 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆55Updated 11 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 3 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆60Updated 4 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.☆282Updated last year
- Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".☆21Updated 4 years ago