statmlben / awesome-statml
This repository contains a list of awesome literature in statistics and machine learning.
☆14Updated 10 months ago
Alternatives and similar repositories for awesome-statml:
Users that are interested in awesome-statml are comparing it to the libraries listed below
- Recommender systems in Python☆27Updated 3 months ago
- Significance tests of feature relevance for a black-box learner☆18Updated 8 months ago
- nl-causal: nonlinear causal inference based on IV regression in Python☆15Updated 9 months ago
- CUHK-SToAT: Open Statistical Toolkits☆19Updated 3 weeks ago
- Python library for Variants of Support Vector Machines☆11Updated 3 years ago
- Course Materials☆12Updated 2 years ago
- This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning].☆11Updated 7 months ago
- Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for sch…☆179Updated 4 months ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆170Updated 11 months ago
- This repository contains a list of awesome literature in learning-to-rank.☆15Updated last year
- Feature selection in neural networks☆236Updated 7 months ago
- A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)☆186Updated 2 months ago
- Repository of the paper "Imperceptible Adversarial Attacks on Tabular Data" presented at NeurIPS 2019 Workshop on Robust AI in Financial …☆15Updated 3 years ago
- Bivariate Shapley is a Shapley-based method of identifying directional feature interactions and feature redundancy☆19Updated last year
- Local explanations with uncertainty 💐!☆40Updated last year
- pyCausalFS:A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆69Updated 4 years ago
- Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"☆24Updated 2 years ago
- BITES: Balanced Individual Treatment Effect for Survival data☆18Updated last year
- ☆223Updated 2 years ago
- ☆16Updated last year
- VAEs and nonlinear ICA: a unifying framework☆47Updated 5 years ago
- ☆27Updated 2 years ago
- Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…☆57Updated last month
- Scaling structural learning with NO-BEARS☆13Updated 5 years ago
- For sharing purposes☆27Updated last year
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆239Updated 2 years ago
- A benchmark for distribution shift in tabular data☆52Updated 10 months ago
- Codebase for VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain - NeurIPS 2020☆147Updated 4 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆148Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆137Updated 10 months ago