vislearn / analyzing_inverse_problems

Related projects: ⓘ

• ELIFE-ASU / INNLab
  A python/pytorch package for invertible neural networks
  ☆56Updated last year
• vislearn / conditional_INNs
  Code for the paper "Guided Image Generation with Conditional Invertible Neural Networks" (2019)
  ☆93Updated 4 years ago
• vislearn / HINT
  Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".
  ☆19Updated 3 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆49Updated last month
• vislearn / inn_toy_data
  Code for artificial toy data sets used to evaluate (conditional) invertible neural networks and related methods
  ☆11Updated 3 years ago
• vislearn / IB-INN
  Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)
  ☆42Updated 4 months ago
• sbarratt / torch_cg
  Preconditioned Conjugate Gradient in Pytorch
  ☆129Updated 7 months ago
• massastrello / awesome-implicit-neural-models
  ☆98Updated 3 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆78Updated 2 years ago
• nlesc-dirac / pytorch
  Improved LBFGS and LBFGS-B optimizers in PyTorch.
  ☆53Updated last week
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆113Updated last year
• xqding / RealNVP
  A PyTorch Implementation of Density Estimation Using Real NVP
  ☆57Updated 3 years ago
• ndahlquist / pytorch-fourier-feature-networks
  Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
  ☆38Updated 4 years ago
• FrederikWarburg / LaplaceAE
  ☆31Updated 2 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆86Updated 5 months ago
• juntang-zhuang / TorchDiffEqPack
  ☆44Updated 10 months ago
• akandykeller / SelfNormalizingFlows
  ☆67Updated last year
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆68Updated last month
• iamalexkorotin / Wasserstein2GenerativeNetworks
  PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)
  ☆49Updated last year
• thegialeo / Training-Invertible-Neural-Networks-as-Autoencoders
  ☆17Updated last year
• nasimrahaman / SpectralBias
  Code for "On the Spectral Bias of Neural Networks", to appear in ICML 2019 (Long Beach, CA).
  ☆102Updated 5 years ago
• pputzky / invertible_rim
  Official Code for "Invert to Learn to Invert" that allows training of invertible networks without storing activations
  ☆36Updated 4 years ago
• jmclong / random-fourier-features-pytorch
  Implementation of "Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains" by Tancik et al.
  ☆77Updated last year
• gngdb / pytorch-minimize
  Use scipy.optimize.minimize as a PyTorch Optimizer.
  ☆63Updated last month
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆82Updated 9 months ago
• aangelopoulos / im2im-uq
  Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…
  ☆50Updated last year
• chenlin9 / Gaussianization_Flows
  ☆21Updated 4 years ago
• noamroze / moser_flow
  ☆15Updated 2 years ago
• tksmatsubara / symplectic-adjoint-method
  Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.
  ☆14Updated 2 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆43Updated 2 years ago