Alternatives and similar repositories for lsat:

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

• rgiordan / paragami
  "Parameter origami" -- folding and unfolding collections of parameters for optimization and sensitivity analysis.
  ☆13Updated last year
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆43Updated 6 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• kd383 / GPML_SLD
  Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)
  ☆18Updated 7 years ago
• MethodsOfMachineLearning / entropy-search
  Entropy Search for Information-Efficient Global Optimization - JMLR v13
  ☆28Updated 7 years ago
• cog-imperial / GPdoemd
  Design of experiments for model discrimination using Gaussian process surrogate models
  ☆36Updated 5 years ago
• LCSL / NystromCoRe
  Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing…
  ☆12Updated 5 years ago
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• danieljtait / ladax
  Layered distributions using FLAX/JAX
  ☆10Updated 4 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆24Updated 5 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• juliusberner / Deep-Multilevel-Kolmogorov-PDE-Solver
  Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation
  ☆12Updated 3 years ago
• cvxgrp / dmcp
  A CVXPY extension for multi-convex programming
  ☆45Updated last year
• boschresearch / PAC_GP
  Implementation of the PAC Bayesian GP learning method.
  ☆10Updated 6 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆26Updated 5 years ago
• GAMES-UChile / BayesianSpectralEstimation
  Bayesian nonparametric spectral estimation
  ☆14Updated 2 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 4 years ago
• QUVA-Lab / COMBO
  ☆47Updated 6 months ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago
• wesg52 / sindy_mio_paper
  Code for Learning Sparse Nonlinear Dynamics via Mixed Integer Optimization
  ☆13Updated 2 years ago
• ghliu / mean-field-fcdnn
  ☆28Updated 5 years ago
• jesserobertson / pydym
  Dynamic mode decomposition in Python
  ☆13Updated 9 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 5 years ago
• anfelopera / lineqGPR
  Gaussian processes regression models with linear inequality constraints
  ☆14Updated 6 months ago
• duvenaud / harlemcmc-shake
  Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.
  ☆37Updated 10 years ago
• gabb7 / AReS-MaRS
  Python 3.6 and TensorFlow implementation of the AReS and MaRS algorithms
  ☆11Updated 5 years ago
• michaelosthege / pyrff
  pyrff: Python implementation of random fourier feature approximations for gaussian processes
  ☆27Updated 2 years ago
• misokg / NIPS2017
  Multi-Information Source Optimization
  ☆22Updated 5 years ago