Alternatives and similar repositories for Rethinking-Calibration-of-Deep-Neural-Networks:

Users that are interested in Rethinking-Calibration-of-Deep-Neural-Networks are comparing it to the libraries listed below

• dengbaowang / Mixup-Inference-in-Training
  This is the implementation of our CVPR'23 paper On the Pitfall of Mixup for Uncertainty Calibration. In the paper, we conduct a series of…
  ☆17Updated 2 years ago
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆43Updated last year
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆55Updated 2 years ago
• Impression2805 / FMFP
  PyTorch implementation of our ECCV 2022 paper "Rethinking Confidence Calibration for Failure Prediction"
  ☆24Updated last year
• deeplearning-wisc / cider
  PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023
  ☆59Updated last year
• alinlab / LfF
  Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)
  ☆91Updated 4 years ago
• RenkunNi / MetaContrastive
  The official code for the publication: "The Close Relationship Between Contrastive Learning and Meta-Learning".
  ☆19Updated 2 years ago
• divyam3897 / UCL
  Code for the paper "Representational Continuity for Unsupervised Continual Learning" (ICLR 22)
  ☆96Updated 2 years ago
• danielchyeh / ImageNet-100-Pytorch
  (Pytorch) Training ResNets on ImageNet-100 data
  ☆56Updated 3 years ago
• VITA-Group / FreeTickets
  [ICLR 2022] "Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity" by Shiwei Liu,…
  ☆27Updated 2 years ago
• tmllab / 2021_NeurIPS_PES
  ☆29Updated 2 years ago
• Vanint / Core-tuning
  This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…
  ☆21Updated 2 years ago
• Impression2805 / OpenMix
  PyTorch implementation of our CVPR2023 paper "OpenMix: Exploring Out-of-Distribution samples for Misclassification Detection"
  ☆24Updated last year
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• mpagli / Agree-to-Disagree
  Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"
  ☆35Updated 2 years ago
• jkatzsam / woods_ood
  ☆16Updated 2 years ago
• db-Lee / selfsup_dd
  Self-Supervised Dataset Distillation for Transfer Learning
  ☆13Updated 11 months ago
• deeplearning-wisc / Spurious_OOD
  ☆22Updated 2 years ago
• kakaoenterprise / Learning-Debiased-Disentangled
  Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"
  ☆101Updated 2 years ago
• zjysteven / MixOE
  [WACV'23] Mixture Outlier Exposure for Out-of-Distribution Detection in Fine-grained Environments
  ☆27Updated last year
• danruod / FS-DGPM
  Code for NeurIPS 2021 paper "Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning".
  ☆16Updated 3 years ago
• m-Just / OoD-Bench
  ☆42Updated 2 years ago
• QizhouWang / DOE
  ☆25Updated 2 years ago
• deeplearning-wisc / vit-spurious-robustness
  ☆24Updated 2 years ago
• Wang-ML-Lab / bayesian-peft
  [NeurIPS 2024] BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
  ☆24Updated 2 months ago
• anniesch / surgical-finetuning
  Code for "Surgical Fine-Tuning Improves Adaptation to Distribution Shifts" published at ICLR 2023
  ☆29Updated last year
• takashiishida / irreducible
  [ICLR 2023] Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classifi…
  ☆20Updated 3 months ago
• kibok90 / imix
  ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
  ☆77Updated last year
• locuslab / tta_conjugate
  Test-Time Adaptation via Conjugate Pseudo-Labels
  ☆39Updated last year
• NeuralCollapseApplications / ImbalancedLearning
  [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnab…
  ☆44Updated 2 years ago