Alternatives and similar repositories for ebm-torch:

Users that are interested in ebm-torch are comparing it to the libraries listed below

• mbilos / stribor
  Library for normalizing flows and neural flows.
  ☆24Updated 2 years ago
• gcucurull / jax-gcn
  Graph Convolutional Networks in JAX
  ☆32Updated 4 years ago
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆76Updated 3 years ago
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆83Updated last year
• mcbal / deep-implicit-attention
  Implementation of deep implicit attention in PyTorch
  ☆65Updated 3 years ago
• stanfordmlgroup / disentanglement
  Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology
  ☆36Updated 4 years ago
• frankhan91 / BSDEEigen
  ☆11Updated 4 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆40Updated 2 years ago
• google-deepmind / flows_for_atomic_solids
  ☆49Updated 2 years ago
• akandykeller / SelfNormalizingFlows
  ☆68Updated 2 years ago
• matbun / EBM--Generative-Energy-Based-Modeling
  Energy Based Models are a quite novel technique for density estimation. In this university project I explore this new research topic and …
  ☆16Updated 3 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆54Updated 4 years ago
• QUVA-Lab / COMBO
  ☆50Updated 8 months ago
• YuGuangWang / PAN
  Path integral based convolution and pooling
  ☆29Updated 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
  ☆24Updated 4 years ago
• gebob19 / introduction_to_normalizing_flows
  Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'
  ☆25Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 8 months ago
• facebookresearch / semi-discrete-flow
  code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"
  ☆26Updated 2 years ago
• swyoon / pytorch-energy-based-model
  Simple illustrative examples for energy-based models in PyTorch
  ☆62Updated 5 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago
• adrienbolens / reinforcement-learning-and-quantum-simulations
  Reinforcement learning applied to digital quantum simulations
  ☆19Updated 5 years ago
• flaport / torch_eunn
  A Pytorch implementation of an efficient unitary neural network (https://arxiv.org/abs/1612.05231)
  ☆33Updated 4 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆72Updated 2 years ago
• dylandoblar / noether-networks
  Meta-learning inductive biases in the form of useful conserved quantities.
  ☆37Updated 2 years ago
• wangleiphy / MongeAmpereFlow
  Continuous-time gradient flow for generative modeling and variational inference
  ☆30Updated 6 years ago
• saparina / neural-ode
  Experiments with Neural Ordinary Differential Equations on image and text classification tasks
  ☆31Updated 6 years ago
• yk / PyTorch_CIFAR10
  Pretrained TorchVision models on CIFAR10 dataset (with weights)
  ☆24Updated 4 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆46Updated last year