Alternatives and similar repositories for Convergence-Rate-NN-Different-Frequencies

Users that are interested in Convergence-Rate-NN-Different-Frequencies are comparing it to the libraries listed below

• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆40Updated 3 years ago
• AaltoML / PeriodicBNN
  Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)
  ☆19Updated 3 years ago
• NBoulle / RationalNets
  Code for the paper "Rational neural networks", NeurIPS 2020
  ☆28Updated 4 years ago
• hmdolatabadi / LRS_NF
  [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".
  ☆20Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• PredictiveIntelligenceLab / LOCA
  ☆14Updated last year
• lorenzrichter / PDE-backward-solver
  ☆21Updated 8 months ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆52Updated 5 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆47Updated last year
• Typal-Research / jacobian_free_backprop
  Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).
  ☆37Updated 3 years ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆38Updated 2 years ago
• DiffEqML / kairos
  Model hub for all your DiffeqML needs. Pretrained weights, modules, and basic inference infrastructure
  ☆25Updated 2 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆53Updated 11 months ago
• xuzhiqin1990 / F-Principle
  code to show F-Principle in the DNN training
  ☆59Updated 2 years ago
• AlexandraVolokhova / stochasticity_in_neural_ode
  "Stochasticity in Neural ODEs: An Empirical Study". Experiments from the paper
  ☆13Updated 5 years ago
• dimitra-maoutsa / odes_for_sdes
  Deterministic particle dynamics for simulating Fokker-Planck probability flows
  ☆24Updated 2 years ago
• juliagusak / neural-ode-metasolver
  Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561
  ☆25Updated 4 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• PredictiveIntelligenceLab / NOMAD
  ☆16Updated 10 months ago
• mohith-sakthivel / mine-pytorch
  Implementation of Information Bottleneck with Mutual Information Neural Estimation (MINE)
  ☆20Updated 4 years ago
• TimRoith / BregmanLearning
  Optimizing neural networks via an inverse scale space flow.
  ☆16Updated last year
• Rose-STL-Lab / Equivariant-Net
  ☆35Updated last year
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆12Updated 3 years ago
• devzhk / cgds-package
  Package for CGD and ACGD optimizers
  ☆20Updated 2 years ago
• FrederikWarburg / LaplaceAE
  ☆32Updated 2 years ago
• ermongroup / self-similarity-prior
  Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations
  ☆28Updated 2 years ago
• elizabethnewman / hessQuik
  Computing gradients and Hessians of feed-forward networks with GPU acceleration
  ☆18Updated last year
• wzhi / ODElearning_INN
  [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks
  ☆10Updated 2 years ago
• PhIMaL / temporal_normalizing_flows
  ☆11Updated 4 years ago