Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"
☆19Mar 31, 2021Updated 5 years ago
Alternatives and similar repositories for dom_adapt
Users that are interested in dom_adapt are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆32Jul 8, 2018Updated 7 years ago
- ☆26Oct 26, 2020Updated 5 years ago
- ☆15Nov 15, 2017Updated 8 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆18Jun 18, 2020Updated 6 years ago
- ☆59Mar 24, 2022Updated 4 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Visualization Collider Effect: ShinyApp☆12Dec 18, 2025Updated 6 months ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Dec 6, 2022Updated 3 years ago
- Adjustment Identification Distance: A gadjid for Causal Structure Learning☆16Apr 23, 2026Updated 2 months ago
- Investigate the speed of adaptation of structural causal models☆16Feb 11, 2021Updated 5 years ago
- An R package for causal discovery in heavy-tailed models☆12Apr 22, 2024Updated 2 years ago
- Reproduce DLOW: Domain Flow for Adaptation and Generalization☆20Jan 31, 2020Updated 6 years ago
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆17Jun 7, 2021Updated 5 years ago
- ☆37Aug 19, 2025Updated 10 months ago
- ☆11Oct 9, 2022Updated 3 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Explainable recommendation via interpretable feature mapping☆19Apr 25, 2020Updated 6 years ago
- Time series data structure learning with NOTEARS and DYNOTEARS☆15May 23, 2024Updated 2 years ago
- Request For Comments de la CPESR : travaux en cours ouverts à la discussion.☆10Jun 25, 2026Updated last week
- Official code of "Where are my Neighbors? Exploiting Patches Relations in Self-Supervised Vision Transformer", Guglielmo Camporese, Elena…☆21Dec 14, 2022Updated 3 years ago
- Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…☆17Nov 12, 2019Updated 6 years ago
- Quantile risk minimization☆26Aug 8, 2024Updated last year
- ☆13Jan 8, 2020Updated 6 years ago
- ☆10Apr 5, 2024Updated 2 years ago
- ☆10Jul 23, 2020Updated 5 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Wasserstein Based Domain Adaptation Model☆46Jan 2, 2019Updated 7 years ago
- Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https:…☆15Nov 2, 2023Updated 2 years ago
- Selection Distribution Generator for Domain Adaptation☆26Aug 24, 2019Updated 6 years ago
- CEVAE(Causal Effect Variational AutoEncoder) written with pytorch and pyro.☆10Feb 15, 2021Updated 5 years ago
- ☆14Jul 5, 2023Updated 2 years ago
- ☆24Oct 24, 2021Updated 4 years ago
- Scalable open-source software to run, develop, and benchmark causal discovery algorithms☆84Jun 21, 2026Updated last week
- ☆25Oct 20, 2025Updated 8 months ago
- Code for ICLR'24 workshop ME-FoMo-How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation☆38Oct 18, 2024Updated last year
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Code to reproduce the case studies of the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan…☆18Jan 3, 2025Updated last year
- R/haldensify: Highly Adaptive Lasso Conditional Density Estimation☆19May 12, 2026Updated last month
- ☆12Jul 17, 2023Updated 2 years ago
- [ACM MM 2019] Code release for "Joint Adversarial Domain Adaptation" https://dl.acm.org/doi/10.1145/3343031.3351070☆19Sep 15, 2020Updated 5 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆24Aug 9, 2019Updated 6 years ago
- Official code for the paper "Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network"☆17Aug 9, 2023Updated 2 years ago
- Targeted Learning entry in the Atlantic Causal Inference Conference's 2017 competition☆12Jul 16, 2017Updated 8 years ago