AmrMKayid / namLinks
Neural Additive Models (Google Research)
☆71Updated 3 years ago
Alternatives and similar repositories for nam
Users that are interested in nam are comparing it to the libraries listed below
Sorting:
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 3 years ago
- PyTorch implementation for Neural Additive Models☆24Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆66Updated 5 months ago
- For calculating Shapley values via linear regression.☆70Updated 4 years ago
- [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets☆86Updated 2 years ago
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆285Updated 2 years ago
- An amortized approach for calculating local Shapley value explanations☆98Updated last year
- A repo for transfer learning with deep tabular models☆104Updated 2 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆77Updated 4 years ago
- Neural Additive Models (Google Research)☆28Updated last year
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 3 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated 11 months ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 4 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆31Updated 3 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆62Updated 5 years ago
- The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"☆145Updated 3 years ago
- Rule Extraction Methods for Interactive eXplainability☆46Updated 3 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆84Updated last year
- A benchmark for distribution shift in tabular data☆55Updated last year
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- ☆61Updated 4 years ago
- Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.☆75Updated 8 months ago
- Diffusion Models for Causal Discovery☆85Updated 2 years ago
- ☆28Updated last year
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆68Updated 8 months ago
- Resources for Machine Learning Explainability☆82Updated 11 months ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆67Updated 2 years ago