Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
☆47Aug 5, 2022Updated 3 years ago
Alternatives and similar repositories for nodegam
Users that are interested in nodegam are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆14Aug 15, 2021Updated 4 years ago
- Neural Additive Models (Google Research)☆75Sep 29, 2021Updated 4 years ago
- PyTorch implementation for Neural Additive Models☆25Dec 2, 2020Updated 5 years ago
- Generalized additive model with pairwise interactions☆69Mar 22, 2024Updated 2 years ago
- Unofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al.☆14May 30, 2021Updated 5 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- CGA2M_plus is a Python package of Constraint GA2M plus(CGA2M+), which we proposed. CGA2M+ is a model that improves GA2M in two respects: …☆17Mar 29, 2026Updated 2 months ago
- ☆11Feb 20, 2021Updated 5 years ago
- A straightforward implementation of EGBM-based Generalized Additive Model☆13Oct 15, 2020Updated 5 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆29Sep 29, 2020Updated 5 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Mar 22, 2023Updated 3 years ago
- ☆11Jul 9, 2021Updated 4 years ago
- NBA stats and analysis☆11Feb 26, 2023Updated 3 years ago
- ☆13May 28, 2021Updated 5 years ago
- Personal coach to help you obtain desired AI decisions!☆20Oct 3, 2023Updated 2 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Gradient boosting on steroids☆28Jun 17, 2024Updated last year
- ☆12Oct 31, 2020Updated 5 years ago
- A mixture density network, by PyTorch, for scikit-learn☆25Feb 27, 2026Updated 3 months ago
- A Natural Language Interface to Explainable Boosting Machines☆71Jul 5, 2024Updated last year
- Generalized Optimal Sparse Decision Trees☆72Mar 20, 2024Updated 2 years ago
- Black Box Optimization Methods☆14Jun 8, 2020Updated 6 years ago
- ☆13Jul 2, 2025Updated 11 months ago
- A process mining library built upon scikit-learn!☆23May 28, 2026Updated last week
- A Python package for process-mining with DECLARE models.☆17Jun 13, 2024Updated last year
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- A package to parse NBA play by play pandas dataframes and calculate statistics☆16Dec 27, 2022Updated 3 years ago
- ☆17Apr 13, 2026Updated last month
- Transformer Network for Predictive Business Process Monitoring Tasks☆47Sep 26, 2024Updated last year
- An extension of Py-Boost to probabilistic modelling☆24Jan 19, 2023Updated 3 years ago
- https://arxiv.org/abs/2009.01561☆23Dec 8, 2022Updated 3 years ago
- Multi-target Random Forest implementation that can mix both classification and regression tasks☆27May 15, 2020Updated 6 years ago
- ☆12Jul 21, 2024Updated last year
- Pydata talk - Football Analytics Using Hierarchical Bayesian Models in PyMC☆25Oct 30, 2021Updated 4 years ago
- TrueSkill Through Time: the Julia, Python and R packages.☆26Feb 3, 2025Updated last year
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Nested Cross-Validation for Bayesian Optimized Gradient Boosting☆20Apr 7, 2020Updated 6 years ago
- An implementation of M5 and model trees in python, compliant with scikit-learn.☆24Jan 22, 2024Updated 2 years ago
- Editing machine learning models to reflect human knowledge and values☆130Oct 3, 2023Updated 2 years ago
- Conformalized Quantile Regression☆310Feb 2, 2026Updated 4 months ago
- This is the official code implementation of Bongard-OpenWorld (ICLR 2024).☆14Jan 6, 2025Updated last year
- ☆16Apr 14, 2021Updated 5 years ago
- Code for paper "Continuous and Distribution-free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach" https:…☆23Feb 22, 2025Updated last year