wilson-ye-chen / sp-mcmcLinks
MATLAB code for Stein Point Markov Chain Monte Carlo.
☆13Updated 6 years ago
Alternatives and similar repositories for sp-mcmc
Users that are interested in sp-mcmc are comparing it to the libraries listed below
Sorting:
- Nonlinear SVGD for Learning Diversified Mixture Models☆13Updated 6 years ago
- The code for Meta Learning for SGMCMC☆25Updated 6 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆14Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆45Updated 6 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago
- Pytorch implementation for "Particle Flow Bayes' Rule"☆14Updated 6 years ago
- ☆22Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆119Updated 2 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Pytorch implementation of Planar Flow☆17Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆56Updated 4 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆16Updated 6 years ago
- ☆50Updated last year
- Deep convolutional gaussian processes.☆80Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- ☆47Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆59Updated 11 months ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 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