Alternatives and similar repositories for scmp:

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

• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆17Updated last year
• js-d / sim_metric
  ☆35Updated last year
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆40Updated 2 years ago
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆20Updated 2 years ago
• a-lucic / focus
  ☆16Updated 2 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 3 years ago
• ykwon0407 / fast_dist_shapley
  Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)
  ☆21Updated last year
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆35Updated 2 years ago
• Zhenyu-LIAO / RMT4ELM
  A Random Matrix Approach to Extreme Learning Machine
  ☆14Updated 7 years ago
• jcperdomo / performative-prediction
  ☆31Updated 3 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆22Updated 2 years ago
• ganguli-lab / degrees-of-freedom
  ☆37Updated 3 years ago
• guanghelee / iclr20-locally-constant-nets
  "Oblique Decision Trees from Derivatives of ReLU Networks" (ICLR 2020, previously called "Locally Constant Networks")
  ☆22Updated 3 years ago
• gd-zhang / noisy-quadratic-model
  Large-batch Training, Neural Network Optimization
  ☆9Updated 5 years ago
• ron-amit / meta-learning-adjusting-priors2
  Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018
  ☆18Updated 4 years ago
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated 11 months ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 9 months ago
• andreeadeac22 / Mila-Graph-Reading-Group
  Weekly reading group on Graph Representation Learning at Mila
  ☆17Updated 5 years ago
• KordingLab / hilbert-constrained-gradient-descent
  Pytorch optimizers implementing Hilbert Constrained Gradient Descent
  ☆19Updated 5 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆26Updated 3 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• AI-secure / KNN-PVLDB
  Official Repo for "Efficient task-specific data valuation for nearest neighbor algorithms"
  ☆26Updated 5 years ago
• tml-epfl / sgd-sparse-features
  SGD with large step sizes learns sparse features [ICML 2023]
  ☆32Updated 2 years ago
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆36Updated last year
• MadryLab / ImageNetMultiLabel
  Fine-grained ImageNet annotations
  ☆29Updated 4 years ago
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆29Updated 6 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• gkdziugaite / pacbayes-opt
  Optimizing PAC-Bayes bounds for Stochastic Neural Networks with Gaussian weights
  ☆27Updated 4 years ago