rgklab / detectron

Related projects: ⓘ

• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated 11 months ago
• aperezlebel / beyond_calibration
  Code of the paper "Beyond calibration: estimating the grouping loss of modern neural networks" published in ICLR 2023.
  ☆10Updated 10 months ago
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆17Updated 6 months ago
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated 4 months ago
• MLforHealth / CXR_Fairness
  Improving the Fairness of Chest X-ray Classifiers
  ☆14Updated 2 years ago
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆27Updated 2 years ago
• cianeastwood / qrm
  Quantile risk minimization
  ☆24Updated last month
• Sulam-Group / h-shap
  h-Shap provides an exact, fast, hierarchical implementation of Shapley coefficients for image explanations
  ☆15Updated 10 months ago
• zhang64-llnl / Mix-n-Match-Calibration
  ☆33Updated 3 years ago
• ZerojumpLine / ModelEvaluationUnderClassImbalance
  [MICCAI2022] Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores.
  ☆11Updated 3 months ago
• izmailovpavel / spurious_feature_learning
  ☆40Updated last year
• NYUMedML / conditional_ssl_hist
  ☆14Updated 2 years ago
• suinleelab / vit-shapley
  ☆24Updated 2 months ago
• ahmedmalaa / evaluating-generative-models
  ☆16Updated last year
• rajevv / Multi_L2D
  Code for Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles [AISTATS'23]
  ☆10Updated last year
• clinicalml / proxy-anchor-regression
  Code for ICML 2021 paper "Regularizing towards Causal Invariance: Linear Models with Proxies" (ICML 2021)
  ☆11Updated 2 years ago
• YannDubs / Invariant-Self-Supervised-Learning
  Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"
  ☆40Updated last year
• QingyuZhao / BR-Net
  ☆46Updated 3 years ago
• JonathanCrabbe / CARs
  This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human con…
  ☆9Updated last year
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 3 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆40Updated 3 months ago
• YannDubs / SSL-Risk-Decomposition
  Benchmark and analysis of 165 pretrained SSL models. Code for "Evaluating Self-Supervised Learning via Risk Decomposition".
  ☆13Updated last year
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆61Updated 4 months ago
• aangelopoulos / conformal-risk
  Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…
  ☆57Updated last year
• mertyg / beyond-confidence-atypicality
  Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
  ☆12Updated 5 months ago
• ieee8023 / latentshift
  A method to generate counterfactuals
  ☆11Updated 4 months ago
• biomedia-mira / chexploration
  Official repository for 'Algorithmic encoding of protected characteristics in chest X-ray disease detection models'
  ☆24Updated last year
• seedatnabeel / Data-SUITE
  Data-SUITE: Data-centric identification of in-distribution incongruous examples (ICML 2022)
  ☆9Updated last year
• biomedia-mira / causal-gen
  (ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models
  ☆54Updated 3 months ago
• opendataval / opendataval
  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
  ☆81Updated last month