mertyg / beyond-confidence-atypicalityLinks
Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
☆13Updated last year
Alternatives and similar repositories for beyond-confidence-atypicality
Users that are interested in beyond-confidence-atypicality are comparing it to the libraries listed below
Sorting:
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆70Updated 11 months ago
- ☆12Updated 2 years ago
- ☆31Updated 4 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- ☆25Updated 3 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆24Updated 3 years ago
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆67Updated 2 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Updated 4 years ago
- Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift☆35Updated 2 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Invariant-feature Subspace Recovery (ISR)☆23Updated 3 years ago
- LISA for ICML 2022☆51Updated 2 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Updated 11 months ago
- ☆46Updated 2 years ago
- This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human con…☆14Updated 3 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆71Updated 2 years ago
- Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…☆22Updated 5 years ago
- ☆32Updated 7 years ago
- ☆44Updated 6 months ago
- Benchmark and analysis of 165 pretrained SSL models. Code for "Evaluating Self-Supervised Learning via Risk Decomposition".☆15Updated 2 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆30Updated 4 years ago
- Quantile risk minimization☆24Updated last year
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.☆18Updated last year
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 3 years ago
- Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning☆44Updated 2 years ago
- ☆10Updated 3 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 4 years ago
- ☆49Updated 2 years ago