henripal / sgldLinks
☆59Updated 6 years ago
Alternatives and similar repositories for sgld
Users that are interested in sgld are comparing it to the libraries listed below
Sorting:
- Limitations of the Empirical Fisher Approximation☆47Updated 3 months ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Normalizing Flows in Jax☆108Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- ☆26Updated 7 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Deep Neural Networks Entropy from Replicas☆33Updated 5 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆71Updated 9 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆104Updated 4 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- ☆54Updated 11 months ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Normalizing Flows using JAX☆83Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 3 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆182Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago