ahmedmalaa / Symbolic-MetamodelingLinks
Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.
☆52Updated 6 years ago
Alternatives and similar repositories for Symbolic-Metamodeling
Users that are interested in Symbolic-Metamodeling are comparing it to the libraries listed below
Sorting:
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆38Updated 4 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated 2 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- ☆15Updated 3 years ago
- Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"☆15Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- A Python package for intrinsic dimension estimation☆94Updated 2 months ago
- General Latent Feature Modeling for Heterogeneous data☆50Updated last year
- "Variational inference tools to leverage estimator sensitivity."☆16Updated 2 years ago
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆37Updated 5 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- My Research Journal covering various topics that interest me. They're mostly scattered notes and resources.☆34Updated 3 years ago
- ☆12Updated 3 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆87Updated last year
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- A lightweight didactic library of kernel methods using the back-end JAX.☆12Updated 2 years ago
- Random feature latent variable models in Python☆23Updated 2 years ago
- Automated Scalable Bayesian Inference☆131Updated 3 years ago
- Computational statistics and machine learning reading group at Imperial College London (2019-2020)☆24Updated last month
- Code for the Causal Bayesian Optimization algorithm (http://proceedings.mlr.press/v108/aglietti20a/aglietti20a.pdf)☆32Updated 5 years ago
- Python package for evaluating model calibration in classification☆20Updated 6 years ago
- ☆53Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago