Alternatives and similar repositories for multiset-equivariance

Users that are interested in multiset-equivariance are comparing it to the libraries listed below

• wgrathwohl / VERA
  ☆64Updated last year
• dylandoblar / noether-networks
  Meta-learning inductive biases in the form of useful conserved quantities.
  ☆37Updated 2 years ago
• ngruver / lie-deriv
  ☆39Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆52Updated 4 years ago
• lzzcd001 / ade-code
  Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)
  ☆13Updated 5 years ago
• jmtomczak / git_flow
  General Invertible Transformations for Flow-based Generative Models
  ☆18Updated 4 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
• katalinic / sdflows
  JAX exponential map normalising flows on sphere
  ☆17Updated 4 years ago
• IndustAI / learning-group-structure
  Code associated with our paper "Learning Group Structure and Disentangled Representations of Dynamical Environments"
  ☆15Updated 2 years ago
• michaelsdr / sinkformers
  Transformers with doubly stochastic attention
  ☆45Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 10 months ago
• maxxxzdn / implicit-steerable-kernels
  Implicit Convolutional Kernels for Steerable CNNs [NeurIPS'23]
  ☆29Updated 3 months ago
• stanfordmlgroup / disentanglement
  Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology
  ☆36Updated 4 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• necludov / action-matching
  Implementation of Action Matching for the Schrödinger equation
  ☆24Updated last year
• wgrathwohl / GWG_release
  Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"
  ☆54Updated last year
• tychovdo / lila
  Code for "Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations"
  ☆23Updated 2 years ago
• AndrewAtanov / semi-supervised-flow-pytorch
  Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"
  ☆10Updated 5 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 2 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• aboustati / vargrad
  Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference
  ☆12Updated 4 years ago
• ermongroup / f-EBM
  Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020
  ☆36Updated 2 years ago
• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆45Updated 2 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆56Updated 4 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• ryoungj / mcbits
  [ICML'21 Oral] Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
  ☆14Updated 3 years ago
• facebookresearch / semi-discrete-flow
  code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"
  ☆26Updated 2 years ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆22Updated 5 years ago
• necludov / iMCMC
  ☆22Updated 4 years ago