e-hulten / maf
PyTorch implementation of the Masked Autoregressive Flow
☆21Updated 3 years ago
Related projects: ⓘ
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆45Updated 3 years ago
- Masked Autoregressive Flow☆198Updated last month
- Official code for the ICLR 2021 paper Neural ODE Processes☆71Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- ☆22Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆27Updated 4 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 3 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 3 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆40Updated last year
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆56Updated 3 years ago
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆16Updated 2 years ago
- A Pytorch Implementation of Attentive Neural Process☆73Updated 5 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆115Updated 9 months ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- SVGD implementation☆10Updated 6 years ago
- The collection of recent papers about variational inference☆84Updated 4 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆78Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 7 months ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆78Updated 5 months ago
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 4 years ago
- Official Implementation of the paper "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"☆16Updated 2 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Gaussian Process Prior Variational Autoencoder☆78Updated 5 years ago
- Featurized Density Ratio Estimation☆19Updated 3 years ago
- Regularized Neural ODEs (RNODE)☆81Updated 3 years ago
- Experiments for Neural Flows paper☆84Updated 2 years ago
- ☆39Updated 2 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 4 years ago
- ☆36Updated 4 years ago