jik0730 / Deep-Mixed-Effect-Model-using-Gaussian-ProcessesLinks
Implementations for "Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare" published on AAAI 2020 (to appear)
☆13Updated 6 years ago
Alternatives and similar repositories for Deep-Mixed-Effect-Model-using-Gaussian-Processes
Users that are interested in Deep-Mixed-Effect-Model-using-Gaussian-Processes are comparing it to the libraries listed below
Sorting:
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆294Updated 2 years ago
- Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)☆91Updated last year
- Python scripts for our model described in http://proceedings.mlr.press/v130/ramchandran21b.html☆16Updated 4 years ago
- VAEs and nonlinear ICA: a unifying framework☆40Updated 5 years ago
- ☆93Updated 2 years ago
- Time-Contrastive Learning☆68Updated 7 years ago
- Gaussian Process Prior Variational Autoencoder☆87Updated 7 years ago
- ☆33Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆67Updated last year
- This repository contains the code used for Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care …☆83Updated 9 months ago
- ☆31Updated 3 years ago
- counterfactuals for magnetic resonance images of multiple sclerosis☆26Updated 4 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- Alignment between clustered datasets via hierarchical Wasserstein distance☆38Updated 2 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Deep Generative ODE Modelling with Known Unknowns☆18Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data☆222Updated 3 years ago
- Dynamical Components Analysis☆33Updated 5 months ago
- ☆18Updated 7 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 6 years ago
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆130Updated 2 years ago
- Scalable python GPU solvers for fused unbalanced gromov-wasserstein optimal transport problems, with routines and examples to align brain…☆46Updated 7 months ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆43Updated 3 years ago
- ☆46Updated 5 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- Code for "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis"☆27Updated 5 years ago
- ☆37Updated 3 years ago