statmlben / awesome-statmlLinks
This repository contains a list of awesome literature in statistics and machine learning.
☆13Updated last year
Alternatives and similar repositories for awesome-statml
Users that are interested in awesome-statml are comparing it to the libraries listed below
Sorting:
- Recommender systems in Python☆28Updated last week
- Significance tests of feature relevance for a black-box learner☆19Updated last year
- nl-causal: nonlinear causal inference based on IV regression in Python☆16Updated last year
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆633Updated 3 years ago
- Python library for Variants of Support Vector Machines☆11Updated 3 years ago
- Bayesian Deep Learning: A Survey☆517Updated this week
- PyTorch implementation of bayesian neural network [torchbnn]☆542Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆147Updated last year
- Must-read papers and resources related to causal inference and machine (deep) learning☆737Updated 2 years ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆739Updated last month
- This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning].☆10Updated last year
- Feature selection in neural networks☆243Updated last year
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆624Updated 5 months ago
- A benchmark for distribution shift in tabular data☆55Updated last year
- Repository of the paper "Imperceptible Adversarial Attacks on Tabular Data" presented at NeurIPS 2019 Workshop on Robust AI in Financial …☆16Updated 3 years ago
- We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NU…☆518Updated 2 years ago
- A data index for learning causality.☆478Updated last year
- Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for sch…☆199Updated 9 months ago
- This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…☆340Updated last year
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,932Updated last year
- The Randomized Conditional Independence Test (RCIT) and the Randomized conditional Correlation Test (RCoT)☆27Updated 6 years ago
- Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"☆24Updated 2 years ago
- A Python package implementing a variety of statistical methods that rely on kernels (e.g. HSIC for independence testing).☆15Updated 3 years ago
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆126Updated last year
- Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…☆61Updated 7 months ago
- Bivariate Shapley is a Shapley-based method of identifying directional feature interactions and feature redundancy☆20Updated 4 months ago
- ☆14Updated last year
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆366Updated last year
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆825Updated 4 years ago
- A simple way to calibrate your neural network.☆1,162Updated 2 months ago