sudiptodip15 / CCMILinks
Classifier based mutual information, conditional mutual information estimation; conditional independence testing
☆34Updated 5 years ago
Alternatives and similar repositories for CCMI
Users that are interested in CCMI are comparing it to the libraries listed below
Sorting:
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 3 years ago
- VAEs and nonlinear ICA: a unifying framework☆47Updated 5 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing☆45Updated last year
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 4 years ago
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆30Updated 4 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Testing methods for estimating KL-divergence from samples.☆64Updated 3 months ago
- ☆32Updated 6 years ago
- Time-Contrastive Learning☆65Updated 7 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆41Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- ☆19Updated 5 years ago
- demonstration of the information bottleneck theory for deep learning☆63Updated 7 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- ☆25Updated last year
- VAEs and nonlinear ICA: a unifying framework☆35Updated 5 years ago
- Difference-of-Entropies (DoE) Estimator☆25Updated 3 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆22Updated 5 years ago
- Discovering directional relations via minimum predictive information regularization☆24Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Code for "Generative causal explanations of black-box classifiers"☆34Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆35Updated 2 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆73Updated 5 years ago
- Benchmarks for Out-of-Distribution Generalization in Time Series Tasks☆69Updated 2 years ago
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆102Updated 5 years ago
- Code for Invariant Rep. Without Adversaries (NIPS 2018)☆35Updated 5 years ago