dobriban / Topics-In-Modern-Statistical-LearningLinks
Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc
☆178Updated last year
Alternatives and similar repositories for Topics-In-Modern-Statistical-Learning
Users that are interested in Topics-In-Modern-Statistical-Learning are comparing it to the libraries listed below
Sorting:
- ☆194Updated 2 years ago
- Resources for education in statistics and machine learning: from advanced undergraduate to research level☆103Updated last year
- A package for conformal prediction with conditional guarantees.☆67Updated 3 months ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated 2 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆75Updated 3 years ago
- Conformalized Quantile Regression☆301Updated 3 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆255Updated 3 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 3 years ago
- A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.☆272Updated 4 months ago
- A statistical toolkit for scientific discovery using machine learning☆79Updated last year
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆45Updated 2 years ago
- A Python toolbox for conformal prediction research on deep learning models, using PyTorch.☆443Updated 2 months ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆73Updated last year
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆86Updated 4 years ago
- Public dataset repository for the Causal Chamber Project☆56Updated 2 months ago
- Short tutorials on the use of machine learning methods for causal inference☆50Updated 3 years ago
- A course on imprecise probabilistic machine learning☆115Updated 2 weeks ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆57Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2022.☆181Updated 3 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆84Updated last year
- CSuite: A Suite of Benchmark Datasets for Causality☆81Updated 2 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆71Updated 11 months ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆162Updated last month
- Neural Additive Models (Google Research)☆74Updated 4 years ago
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆174Updated last year
- Conditional calibration of conformal p-values for outlier detection.☆38Updated 3 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆88Updated last year
- [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets☆88Updated 2 years ago
- Lightweight, useful implementation of conformal prediction on real data.☆1,007Updated 2 months ago
- Active Bayesian Causal Inference (Neurips'22)☆59Updated last year