d909b / ameLinks
🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of feature importance for individual samples.
☆42Updated 2 years ago
Alternatives and similar repositories for ame
Users that are interested in ame are comparing it to the libraries listed below
Sorting:
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- ☆32Updated 7 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 5 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆62Updated 5 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- ☆91Updated 2 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- ☆17Updated 6 years ago
- ☆65Updated last year
- ☆29Updated 6 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE☆40Updated 2 years ago
- Causal Inference & Deep Learning, MIT IAP 2018☆89Updated 7 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 4 years ago
- Reproduction work of "Neural Relational Inference for Interacting Systems" in Chainer☆34Updated 6 years ago
- A short course on temporal point process and modeling irregular time series☆21Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Tools for robustness evaluation in interpretability methods☆10Updated 4 years ago
- Code for "Generative causal explanations of black-box classifiers"☆34Updated 4 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆22Updated 2 years ago
- ☆25Updated 2 years ago