cicl-stanford / csm
Contains all materials for the paper "A counterfactual simulation model of causal judgment".
☆23Updated 3 years ago
Alternatives and similar repositories for csm:
Users that are interested in csm are comparing it to the libraries listed below
- Code for "Neural causal learning from unknown interventions"☆100Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆29Updated 3 years ago
- Python implementation of Bayesian Program Learning tools (with PyTorch)☆72Updated 2 years ago
- ☆22Updated last year
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).☆21Updated 6 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆29Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 3 years ago
- Code for the benchmark containing dataset, models and metrics for productive concept learning -- a kind of compositional reasoning task t…☆17Updated 3 years ago
- ☆11Updated 8 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated 2 years ago
- ☆29Updated 6 years ago
- Public Release of Plan2vec Implementation in pyTorch☆56Updated 2 years ago
- ☆17Updated last year
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆92Updated 3 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.☆21Updated 4 years ago
- Variational Reinforcement Learning☆16Updated 5 months ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 4 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Updated 10 years ago
- Active inference implementation of dynamic multi-armed bandits☆18Updated last year
- A toolbox for inference of mixture models☆16Updated last year
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆43Updated 5 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Causal Inference & Deep Learning, MIT IAP 2018☆85Updated 6 years ago
- Code for "Towards a learning theory of cause-effect inference" (ICML 2015).☆29Updated 4 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆20Updated 3 years ago
- This packages provides a simple python implementation of Invariant Causal Prediction (ICP)☆13Updated 9 months ago