Alternatives and similar repositories for analyzing_inverse_problems

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

• ELIFE-ASU / INNLab
  A python/pytorch package for invertible neural networks
  ☆68Updated 2 years ago
• ComputationalRadiationPhysics / InFlow
  ☆11Updated 4 years ago
• vislearn / HINT
  Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".
  ☆21Updated 4 years ago
• vislearn / conditional_INNs
  Code for the paper "Guided Image Generation with Conditional Invertible Neural Networks" (2019)
  ☆101Updated 5 years ago
• zabaras / inn-surrogate
  Solving inverse problems using conditional invertible neural networks.
  ☆33Updated 4 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆57Updated last year
• vislearn / inn_toy_data
  Code for artificial toy data sets used to evaluate (conditional) invertible neural networks and related methods
  ☆12Updated 4 years ago
• BensonRen / BDIMNNA
  ☆22Updated last year
• vislearn / IB-INN
  Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)
  ☆43Updated last year
• xqding / RealNVP
  A PyTorch Implementation of Density Estimation Using Real NVP
  ☆78Updated 4 years ago
• sbarratt / torch_cg
  Preconditioned Conjugate Gradient in Pytorch
  ☆141Updated last year
• FrederikWarburg / LaplaceAE
  ☆32Updated 3 years ago
• Typal-Research / jacobian_free_backprop
  Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).
  ☆39Updated 3 years ago
• Era-Dorta / tf_mvg
  Multivariate Gaussian distributions for Tensorflow.
  ☆23Updated 5 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.
  ☆103Updated this week
• patrick-kidger / torchcubicspline
  Interpolating natural cubic splines. Includes batching, GPU support, support for missing values, evaluating derivatives of the spline, an…
  ☆272Updated 3 years ago
• iamalexkorotin / Wasserstein2GenerativeNetworks
  PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)
  ☆57Updated 2 years ago
• HeSunPU / DPI
  Deep Probabilistic Imaging (DPI): Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging
  ☆38Updated 3 years ago
• LukasRinder / normalizing-flows
  Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
  ☆147Updated last month
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆238Updated 7 years ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆231Updated 5 years 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…
  ☆58Updated 2 years ago
• pputzky / invertible_rim
  Official Code for "Invert to Learn to Invert" that allows training of invertible networks without storing activations
  ☆37Updated 5 years ago
• shirleyzhu233 / realNVP
  PyTorch implementation of realNVP
  ☆90Updated last year
• nlesc-dirac / pytorch
  Improved LBFGS and LBFGS-B optimizers in PyTorch.
  ☆65Updated last year
• massastrello / awesome-implicit-neural-models
  ☆105Updated 4 years ago
• xuzhiqin1990 / F-Principle
  code to show F-Principle in the DNN training
  ☆59Updated 3 years ago
• vdeborto / cdsb
  ☆24Updated 3 years ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆40Updated 2 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 4 years ago