ahmedmalaa / Symbolic-MetamodelingLinks
Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.
☆51Updated 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:
- "Variational inference tools to leverage estimator sensitivity."☆16Updated 2 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- General Latent Feature Modeling for Heterogeneous data☆50Updated last year
- ☆53Updated 2 years ago
- Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."☆46Updated 6 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- ☆15Updated 3 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆87Updated last year
- Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"☆15Updated 3 years ago
- ☆50Updated last year
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆37Updated 5 years ago
- Random feature latent variable models in Python☆23Updated 2 years ago
- ❓y0 (pronounced "why not?") is for causal inference in Python☆63Updated last week
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Talks from Neil Lawrence☆54Updated last year
- #UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning☆12Updated 3 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation☆67Updated 3 years ago
- Python implementation of smooth optimal transport.☆60Updated 4 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆54Updated 4 years ago
- ☆12Updated 3 years ago
- Automated Scalable Bayesian Inference☆131Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆37Updated 2 years ago