authors-1901-10912 / A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-MechanismsView on GitHub
Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"
☆127Jan 31, 2019Updated 7 years ago
Alternatives and similar repositories for A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms
Users that are interested in A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code for "Neural causal learning from unknown interventions"☆103Jul 8, 2020Updated 5 years ago
- ☆64Jul 25, 2024Updated last year
- Code for "Recurrent Independent Mechanisms"☆121Mar 24, 2022Updated 4 years ago
- Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)☆102Jan 13, 2022Updated 4 years ago
- ☆63Sep 29, 2020Updated 5 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.
- The Shape of Data: Intrinsic Distance for Comparing Data Distributions☆12Sep 25, 2019Updated 6 years ago
- Code for paper Causal Confusion in Imitation Learning☆46Dec 17, 2019Updated 6 years ago
- Accompanying code for the paper "Learning Causal Models Online"☆23Jul 14, 2020Updated 5 years ago
- Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"☆205Jul 25, 2024Updated last year
- This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):☆54May 1, 2025Updated last year
- Nauka is a collection of utilities for scientific experiments.☆15Jul 27, 2022Updated 3 years ago
- A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.☆415Sep 10, 2020Updated 5 years ago
- An Empirical Study of Invariant Risk Minimization☆27Jul 6, 2020Updated 5 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆41Nov 12, 2020Updated 5 years ago
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- Implements the Messenger environment and EMMA model.☆25Jun 14, 2023Updated 2 years ago
- Unsupervised Disentanglement Representation Learning in Chainer☆20Mar 24, 2023Updated 3 years ago
- ☆79Apr 17, 2025Updated last year
- [WNGT(2019)] On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation☆11Apr 27, 2022Updated 4 years ago
- ☆13Dec 6, 2018Updated 7 years ago
- Investigate the speed of adaptation of structural causal models☆16Feb 11, 2021Updated 5 years ago
- Official code of the paper "BISCUIT: Causal Representation Learning from Binary Interactions" (UAI 2023)☆39Mar 12, 2024Updated 2 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Dec 3, 2018Updated 7 years ago
- Latent Dynamics Mixture, NeurIPS 2021☆18Oct 25, 2022Updated 3 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- PyTorch code to run synthetic experiments.☆435Sep 8, 2021Updated 4 years ago
- Contrastive Learning of Structured World Models☆397Jun 3, 2020Updated 5 years ago
- A repository to introduce the algorithmic information theory. You could learn what is Kolmogorov complexity and why it is important here.☆13Jul 23, 2025Updated 10 months ago
- A Causal Decision Tree algorithm for causality inference with continuous variables☆23Jan 15, 2021Updated 5 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Dec 5, 2021Updated 4 years ago
- ☆85May 29, 2019Updated 7 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Jul 3, 2019Updated 6 years ago
- This is the oficial repository for "Safer-Instruct: Aligning Language Models with Automated Preference Data"☆17Feb 22, 2024Updated 2 years ago
- Codebase for "Causal Induction from Visual Observations for Goal-Directed Tasks"☆14Feb 25, 2020Updated 6 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.
- Non-stationary Off-policy Evaluation☆13Nov 8, 2018Updated 7 years ago
- An index of algorithms for learning causality with data☆3,266Jan 22, 2025Updated last year
- Implementation of: Kristiadi, Agustinus, and Asja Fischer. "Predictive Uncertainty Quantification with Compound Density Networks." (2019)…☆16May 26, 2022Updated 4 years ago
- Conditional Theorem Proving☆54Apr 30, 2021Updated 5 years ago
- Pytorch package for geometric softmax☆12Jun 13, 2019Updated 6 years ago
- Counterfactual Evaluation and Learning for Interactive Systems: Foundations, Implementations, and Recent Advances☆12Aug 14, 2022Updated 3 years ago
- Official Implementation of Knowledge Flow Prompting☆35Oct 20, 2025Updated 7 months ago