Alternatives and similar repositories for awesome-statml

Users that are interested in awesome-statml are comparing it to the libraries listed below

• statmlben / nonlinear-causal
  nl-causal: nonlinear causal inference based on IV regression in Python
  ☆16Updated last year
• statmlben / dnn-inference
  Significance tests of feature relevance for a black-box learner
  ☆20Updated last year
• jvpoulos / causal-ml
  Must-read papers and resources related to causal inference and machine (deep) learning
  ☆744Updated 3 years ago
• tengyuma / cs229m_notes
  ☆240Updated 2 years ago
• AlaaLab / deep-learning-uncertainty
  Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…
  ☆635Updated 3 years ago
• Liao-Xu / DDR
  This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning].
  ☆11Updated last year
• ericstrobl / RCIT
  The Randomized Conditional Independence Test (RCIT) and the Randomized conditional Correlation Test (RCoT)
  ☆29Updated 6 years ago
• davinhill / BivariateShapley
  Bivariate Shapley is a Shapley-based method of identifying directional feature interactions and feature redundancy
  ☆20Updated 7 months ago
• dplecko / CFA
  Causal Fairness Analysis
  ☆20Updated 8 months ago
• WeiHuang05 / Awesome-Feature-Learning-in-Deep-Learning-Thoery
  Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for sch…
  ☆202Updated last year
• lasso-net / lassonet
  Feature selection in neural networks
  ☆248Updated last year
• leiwu0 / course.math_theory_nn
  Summer course on mathematical theory of deep learning
  ☆53Updated 6 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆57Updated last year
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• statmlben / Variant-SVM
  Python library for Variants of Support Vector Machines
  ☆11Updated 4 years ago
• facebookresearch / InvariantRiskMinimization
  PyTorch code to run synthetic experiments.
  ☆431Updated 4 years ago
• js05212 / BayesianDeepLearning-Survey
  Bayesian Deep Learning: A Survey
  ☆517Updated 2 months ago
• yandex-research / rtdl
  Research on Tabular Deep Learning: Papers & Packages
  ☆1,088Updated last year
• nimarb / pytorch_influence_functions
  This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…
  ☆344Updated 2 years ago
• juangamella / ges
  Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…
  ☆61Updated 9 months ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆153Updated last year
• anpwu / Causal4Application
  ☆26Updated 3 years ago
• YyzHarry / imbalanced-regression
  [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
  ☆902Updated 3 years ago
• geoopt / geoopt
  Riemannian Adaptive Optimization Methods with pytorch optim
  ☆1,020Updated 4 months ago
• ENSTA-U2IS-AI / awesome-uncertainty-deeplearning
  This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…
  ☆775Updated 3 weeks ago
• gpleiss / temperature_scaling
  A simple way to calibrate your neural network.
  ☆1,166Updated 5 months ago
• JacobHelwig / covdepGE
  A covariate-dependent approach to Gaussian graphical modeling in R
  ☆23Updated 2 months ago
• criteo-research / continuous-fairness
  ☆22Updated 6 years ago
• yandex-research / rtdl-revisiting-models
  (NeurIPS 2021) Revisiting Deep Learning Models for Tabular Data
  ☆310Updated last year
• YuhangZhou88 / ESL_Solution
  ☆286Updated 3 years ago