Alternatives and similar repositories for opt_methods

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

• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 4 months ago
• pnkraemer / probfindiff
  Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…
  ☆11Updated 2 years ago
• AlexandraVolokhova / stochasticity_in_neural_ode
  "Stochasticity in Neural ODEs: An Empirical Study". Experiments from the paper
  ☆13Updated 5 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• QB3 / sparse-ho
  Fast hyperparameter settings for non-smooth estimators:
  ☆40Updated 2 years ago
• pnkraemer / tornadox
  Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…
  ☆21Updated last year
• probabilistic-numerics / probnum-spring-school
  Tutorial materials of the Probabilistic Numerics Spring School.
  ☆35Updated 2 years ago
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆50Updated 4 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆114Updated 6 months ago
• kazukiosawa / ngd_in_wide_nn
  simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…
  ☆15Updated 4 years ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆52Updated last year
• MilesCranmer / sympy2jax
  Turning SymPy expressions into JAX functions
  ☆45Updated 4 years ago
• elizabethnewman / hessQuik
  Computing gradients and Hessians of feed-forward networks with GPU acceleration
  ☆20Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆20Updated 3 years ago
• ymalitsky / adaptive_GD
  Adaptive gradient descent without descent
  ☆48Updated 3 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆48Updated 4 years ago
• ucl-bug / jaxdf
  A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
  ☆129Updated last year
• IdanAchituve / GDKL
  Code that accompanies the paper Guided Deep Kernel Learning
  ☆10Updated 2 years ago
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆69Updated 4 months ago
• COR-OPT / SuperPolyak.py
  Pytorch implementation of SuperPolyak subgradient method.
  ☆43Updated 2 years ago
• pnkraemer / probdiffeq
  Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…
  ☆53Updated last week
• bremen79 / parameterfree
  Parameter-Free Optimizers for Pytorch
  ☆130Updated last year
• lorenzrichter / PDE-backward-solver
  ☆22Updated 10 months ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆139Updated 3 months ago
• f-dangel / phd-thesis
  Source code for my PhD thesis: Backpropagation Beyond the Gradient
  ☆20Updated 2 years ago
• stefanosele / GPfY
  Gaussian processes with spherical harmonic features in JAX
  ☆15Updated 3 weeks ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆78Updated last year
• pnkraemer / matfree
  Matrix-free linear algebra in JAX.
  ☆140Updated 3 weeks ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆35Updated 3 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year