VirgiAgl / DAG-GP
Code for the paper Multi-task Causal Learning with Gaussian Processes (https://arxiv.org/pdf/2009.12821.pdf)
β12Updated 4 years ago
Alternatives and similar repositories for DAG-GP:
Users that are interested in DAG-GP are comparing it to the libraries listed below
- Code for the Causal Bayesian Optimization algorithm (http://proceedings.mlr.press/v108/aglietti20a/aglietti20a.pdf)β29Updated 4 years ago
- π€Ώ Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0β26Updated last year
- β32Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"β82Updated 8 months ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"β25Updated 3 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.β38Updated 2 years ago
- Code for the paper Gaussian process behaviour in wide deep networksβ48Updated 6 years ago
- Training quantile modelsβ43Updated 3 months ago
- β37Updated 6 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)β52Updated 4 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by AdriΓ Garriga-Alonso, Carl Rasmussen and Laurence Aitchβ¦β32Updated 4 years ago
- Recyclable Gaussian Processesβ11Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)β48Updated 5 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831β36Updated 2 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learningβ20Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"β31Updated 4 years ago
- Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testingβ46Updated last year
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlβ66Updated 3 months ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Designβ30Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"β57Updated 3 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processesβ41Updated 7 months ago
- Non-stationary spectral mixture kernels implemented in GPflowβ28Updated 6 years ago
- Accompanying code for AAAI 2021 publication - High-Dimensional Bayesian Optimization via Tree-Structured Additive Modelsβ11Updated 8 months ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problemsβ31Updated 2 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.β37Updated 11 months ago
- Dynamic causal Bayesian optimisationβ35Updated last year
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'β27Updated 3 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)β20Updated 5 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).β48Updated 3 years ago
- β42Updated 6 years ago