Alternatives and similar repositories for NeuralODE

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

• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆54Updated 5 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆102Updated 7 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 7 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆49Updated 9 months ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆88Updated 3 years ago
• dilinwang820 / nonlinear_svgd
  Nonlinear SVGD for Learning Diversified Mixture Models
  ☆13Updated 6 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆36Updated 5 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆30Updated 6 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆57Updated 4 years ago
• cunningham-lab / igr
  ☆30Updated 5 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆112Updated 6 years ago
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆130Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 4 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 4 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆78Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆82Updated 6 years ago
• wilson-ye-chen / sp-mcmc
  MATLAB code for Stein Point Markov Chain Monte Carlo.
  ☆13Updated 6 years ago
• 2prime / LM-ResNet
  Code For Beyond Finite Layer Neural Network:Bridging Deep Architects and Numerical Differential Equations
  ☆15Updated 6 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆42Updated 3 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆60Updated 6 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated last year
• modestyachts / neural_kernels_code
  ☆35Updated 4 years ago
• ermongroup / mintnet
  MintNet: Building Invertible Neural Networks with Masked Convolutions
  ☆40Updated 5 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆77Updated last year
• bobby-he / Neural_Tangent_Kernel
  ☆68Updated 6 years ago