anndvision / causal-baldLinks
☆13Updated last year
Alternatives and similar repositories for causal-bald
Users that are interested in causal-bald are comparing it to the libraries listed below
Sorting:
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆22Updated 2 years ago
- ☆18Updated last year
- Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.☆20Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- Uncertainty in Conditional Average Treatment Effect Estimation☆32Updated 4 years ago
- Benchmark functions for Bayesian optimization☆33Updated last year
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- Random feature latent variable models in Python☆22Updated last year
- Project on Causal Machine learning CS 7290☆16Updated 5 years ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆31Updated 2 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated last year
- A library for uncertainty quantification based on PyTorch☆121Updated 3 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆86Updated last year
- Bayesian optimization with conformal coverage guarantees☆28Updated 2 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- ☆37Updated 3 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆57Updated last year
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆32Updated 3 years ago
- Probabilistic deep learning using JAX☆14Updated 3 months ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- ☆11Updated 6 years ago
- Quantification of Uncertainty with Adversarial Models☆29Updated last year
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago