SeyoungKimLab / DMGP
Official Implementation of "Doubly Mixed-Effects Gaussian Process Regression" (Jun Ho Yoon, Daniel P. Jeong, Seyoung Kim) (AISTATS 2022, Oral)
☆11Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for DMGP
- Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems☆21Updated 2 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Discovering directional relations via minimum predictive information regularization☆23Updated 4 years ago
- Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.☆8Updated 4 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆43Updated 2 years ago
- Codebase for "Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series"☆13Updated 4 years ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆25Updated 2 years ago
- ☆30Updated 6 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆24Updated 3 years ago
- Uncertainty-aware classification.☆14Updated 2 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆28Updated 3 years ago
- Training quantile models☆40Updated 3 years ago
- Influence Estimation for Gradient-Boosted Decision Trees☆25Updated 5 months ago
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆12Updated 3 years ago
- Vector Quantile Regression☆19Updated last year
- Official Implementation of the paper "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"☆17Updated 3 years ago
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 3 years ago
- Code for the Causal Bayesian Optimization algorithm (http://proceedings.mlr.press/v108/aglietti20a/aglietti20a.pdf)☆27Updated 4 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆37Updated 8 months ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆34Updated 5 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆38Updated last year
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆19Updated last year
- Code for "Neural causal learning from unknown interventions"☆99Updated 4 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆80Updated 7 months ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆31Updated last year
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆80Updated 2 years ago