Alternatives and similar repositories for scikit-ntk:

Users that are interested in scikit-ntk are comparing it to the libraries listed below

• aradha / recursive_feature_machines
  ☆46Updated last week
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆63Updated 2 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 2 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆43Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 8 months ago
• rgklab / StructuredNNs
  Structured Neural Networks
  ☆14Updated 11 months ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• jongharyu / neural-svd
  ☆16Updated 7 months ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 4 years ago
• jamesvuc / jax-bayes
  Bayesian inference with Python and Jax.
  ☆32Updated 2 years ago
• neildhir / DCBO
  Dynamic causal Bayesian optimisation
  ☆36Updated 2 years ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆48Updated last year
• jjcherian / conditional-conformal
  A package for conformal prediction with conditional guarantees.
  ☆54Updated 2 months ago
• IDSIA / neuraldiffeq-fwp
  Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…
  ☆22Updated 2 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 3 years ago
• isgibbs / DtACI
  ☆17Updated 2 weeks ago
• steveazzolin / gdl_tutorial_turinginst
  Material for the hands-on tutorial on Graph Deep Learning held at the Alan Turing Institute
  ☆57Updated last year
• msesia / arc
  Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems
  ☆31Updated 2 years ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆27Updated 2 years ago
• msesia / chr
  Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
  ☆22Updated 3 years ago
• fbach2000 / Learning_Theory_from_First_Principles
  Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach
  ☆103Updated last year
• tijana-zrnic / active-inference
  ☆13Updated last year
• rpatrik96 / nl-causal-representations
  This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…
  ☆18Updated 7 months ago
• requeima / llm_processes
  ☆58Updated 3 weeks ago
• FilippoMB / Total-variation-graph-neural-networks
  Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.
  ☆20Updated last month
• KindXiaoming / Omnigrok
  Omnigrok: Grokking Beyond Algorithmic Data
  ☆55Updated 2 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆87Updated 3 years ago
• aangelopoulos / conformal-risk
  Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…
  ☆66Updated 2 years ago