vanderschaarlab / evaluating-generative-modelsLinks
☆31Updated 2 years ago
Alternatives and similar repositories for evaluating-generative-models
Users that are interested in evaluating-generative-models are comparing it to the libraries listed below
Sorting:
- A package for conformal prediction with conditional guarantees.☆67Updated last month
- For calculating Shapley values via linear regression.☆71Updated 4 years ago
- Conditional calibration of conformal p-values for outlier detection.☆37Updated 3 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆72Updated 2 years ago
- ☆14Updated 3 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 3 years ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆176Updated last year
- [Python] Comparison of empirical probability distributions. Integral probability metrics (e.g. Kantorovich metric). f-divergences (e.g. K…☆11Updated 2 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated 4 months ago
- A Python package for unwrapping ReLU DNNs☆68Updated last year
- Repository for the results of my master thesis, about the generation and evaluation of synthetic data using GANs☆45Updated 2 years ago
- Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)☆153Updated 3 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆29Updated 5 years ago
- ☆15Updated 3 years ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆33Updated 2 years ago
- An amortized approach for calculating local Shapley value explanations☆103Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆71Updated last year
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Multi-Objective Counterfactuals☆42Updated 3 years ago
- ☆109Updated 3 years ago
- Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.☆77Updated last year
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- Neural Additive Models (Google Research)☆73Updated 4 years ago
- (ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles☆95Updated 5 months ago
- Model Agnostic Counterfactual Explanations☆88Updated 3 years ago
- A curated list of Robust Machine Learning papers/articles and recent advancements.☆33Updated 3 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 11 months ago
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆174Updated last year
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆42Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆37Updated 2 years ago