lwehbe / 10606607_M20Links
☆14Updated 4 years ago
Alternatives and similar repositories for 10606607_M20
Users that are interested in 10606607_M20 are comparing it to the libraries listed below
Sorting:
- Random feature latent variable models in Python☆22Updated last year
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- Conceptual & empirical comparisons between decision forests & deep networks☆18Updated 3 weeks ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆22Updated 2 years ago
- Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561☆25Updated 4 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆28Updated 4 years ago
- Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.☆20Updated 2 years ago
- Material for STATS271: Applied Bayesian Statistics (Spring 2021)☆26Updated 4 years ago
- Pytorch implementation for "Particle Flow Bayes' Rule"☆14Updated 6 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Contains all materials for the paper "A counterfactual simulation model of causal judgment".☆24Updated 3 years ago
- A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.☆22Updated 5 years ago
- Bounding causal effects in general (continuous, non-additive) instrumental variable models.☆14Updated last year
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆26Updated 4 years ago
- Duke Machine Learning Winter School 2019☆27Updated 6 years ago
- STATS305C: Applied Statistics III (Spring, 2023)☆26Updated 2 years ago
- JAX implementation of Graph Attention Networks☆13Updated 3 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…☆24Updated 8 months ago
- This repo will be an effort to learn and implement some of the milestone papers and models in Deep Learning based language models.☆11Updated 2 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 5 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆21Updated 4 years ago
- Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)☆45Updated 3 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆20Updated 5 years ago
- Kernel Instrumental Variable Regression☆9Updated 4 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆22Updated 11 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆22Updated 4 years ago
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆44Updated 6 years ago
- Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology☆36Updated 4 years ago