Alternatives and similar repositories for experiments_neurips:

Users that are interested in experiments_neurips are comparing it to the libraries listed below

• kartikgupta-at-anu / spline-calibration
  Code implementation of our ICLR'21 paper "Calibration of Neural Networks using Splines"
  ☆21Updated last year
• boschresearch / hierarchical_anomaly_detection
  Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…
  ☆41Updated 4 years ago
• aviralkumar2907 / MMCE
  ☆19Updated 6 years ago
• bat-sheva / Conformal-Learning
  ☆21Updated 2 years ago
• zalanborsos / bilevel_coresets
  Coresets via Bilevel Optimization
  ☆65Updated 4 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago
• geifmany / uncertainty_ICLR
  Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019
  ☆13Updated 5 years ago
• VectorInstitute / gram-ood-detection
  ☆46Updated 4 years ago
• uiuctml / ISR
  Invariant-feature Subspace Recovery (ISR)
  ☆23Updated 2 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆37Updated 3 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆55Updated 2 years ago
• Angie-Liu / labelshift
  Regularized Learning under label shifts
  ☆18Updated 5 years ago
• wronnyhuang / gen-viz
  Code for the paper "Understanding Generalization through Visualizations"
  ☆60Updated 4 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆27Updated 3 years ago
• microsoft / Domain-Adaptation-with-Conditional-Distribution-Matching-and-Generalized-Label-Shift
  Code for the paper Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
  ☆37Updated 4 years ago
• stanford-futuredata / sinkhorn-label-allocation
  Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…
  ☆53Updated 3 years ago
• jfc43 / informative-outlier-mining
  We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…
  ☆56Updated 2 years ago
• KaosEngineer / PriorNetworks
  ☆66Updated 5 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆85Updated 2 years ago
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆39Updated last year
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆41Updated last year
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆30Updated 4 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆82Updated 3 years ago
• p-lambda / gradual_domain_adaptation
  ☆35Updated 3 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆72Updated 2 years ago
• capybaralet / REx_code_release
  ☆64Updated 4 years ago
• zhang64-llnl / Mix-n-Match-Calibration
  ☆34Updated 4 years ago
• mertyg / beyond-confidence-atypicality
  Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
  ☆12Updated 9 months ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year