jungtaekkim / bayeso-benchmarksLinks
Benchmark functions for Bayesian optimization
☆37Updated last year
Alternatives and similar repositories for bayeso-benchmarks
Users that are interested in bayeso-benchmarks are comparing it to the libraries listed below
Sorting:
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆34Updated 3 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 3 years ago
- ☆54Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 6 months ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆42Updated 3 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- ☆67Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆37Updated 4 years ago
- ☆50Updated last year
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆85Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆64Updated last year
- Implementation of Normalizing flows on MNIST https://arxiv.org/abs/1505.05770☆14Updated 6 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 3 months ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- ☆50Updated 4 years ago
- Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"☆13Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago