Alternatives and similar repositories for df-dn-paper

Users that are interested in df-dn-paper are comparing it to the libraries listed below

• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆28Updated 5 years ago
• dmilios / dirichletGPC
  ☆17Updated 6 years ago
• CalculatedContent / ww-trends-2020
  ☆18Updated 4 years ago
• kamilest / brain-age-gnn
  Implementation for Stankevičiūtė et al. "Population graph GNNs for brain age prediction". GRL+ Workshop, ICML 2020.
  ☆40Updated last month
• hichamjanati / mutar
  Multi-task regression in Python
  ☆25Updated 4 years ago
• clinicalml / proxy-anchor-regression
  Code for ICML 2021 paper "Regularizing towards Causal Invariance: Linear Models with Proxies" (ICML 2021)
  ☆11Updated 3 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆23Updated 2 years ago
• yuachen / CausalDA
  Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…
  ☆18Updated 4 years ago
• BouchardLab / pyuoi
  The Union of Intersections Framework in Python
  ☆14Updated this week
• XanderJC / medkit-learn
  The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation (NeurIPS 2021) by Alex J. Chan, Ioana Bica, Alihan Huyuk…
  ☆29Updated 3 years ago
• neuroailab / lr-identify
  A large database of artificial neural network statistics during training
  ☆15Updated 4 years ago
• fraenkel-lab / mogp
  Mixture of Gaussian Processes Model for Sparse Longitudinal Data
  ☆38Updated 2 years ago
• wiseodd / lula
  Companion code for the paper "Learnable Uncertainty under Laplace Approximations" (UAI 2021).
  ☆20Updated 4 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 7 years ago
• rpatrik96 / nl-causal-representations
  This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…
  ☆19Updated last year
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• mlhcmit / edx-materials
  Contains public materials for students enrolled in MITx: 6.871x, Machine Learning for Healthcare
  ☆20Updated 4 years ago
• tijana-zrnic / active-inference
  ☆16Updated last year
• juntang-zhuang / explain_invertible
  repo for "Decision explanation and feature importance for invertible networks"
  ☆14Updated 5 years ago
• adalca / papago
  patch-based gaussian mixture model
  ☆15Updated 6 years ago
• Yu-Group / clinical-rule-vetting
  Learning clinical-decision rules with interpretable models.
  ☆20Updated 2 years ago
• raamana / missingdata
  missing data handing: visualize and impute
  ☆18Updated 6 years ago
• schackv / shapewarp
  Contains tools for generalized Procrustes analysis, active shape models and shape-based image warping
  ☆10Updated 11 years ago
• neurodata / ProgLearn
  NeuroData's package for exploring and using progressive learning algorithms
  ☆38Updated 7 months ago
• layer6ai-labs / UoMH
  ☆12Updated 2 years ago
• wilsonjr / ClusterShapley
  Explaining dimensionality results using SHAP values
  ☆55Updated 9 months ago
• raamana / kernelmethods
  Foundational library for Kernel methods in pattern analysis and machine learning
  ☆43Updated 2 years ago
• preprocessed-connectomes-project / adhd200
  ADHD200 preprocessed
  ☆19Updated 4 years ago
• GaelVaroquaux / ml_med_imaging_failures
  Failures in machine learning for medical imaging
  ☆31Updated 3 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