Alternatives and similar repositories for MonotoneFlows

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

• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆16Updated 7 months ago
• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆80Updated 10 months ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆29Updated 10 months ago
• necludov / action-matching
  Implementation of Action Matching for the Schrödinger equation
  ☆24Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• anh-tong / fractional_neural_sde
  Fractional White Noises for Neural Stochastic Differential Equations (NeurIPS 2022)
  ☆15Updated 2 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• martius-lab / beta-nll
  beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022
  ☆44Updated 3 years ago
• DiffEqML / kairos
  Model hub for all your DiffeqML needs. Pretrained weights, modules, and basic inference infrastructure
  ☆25Updated 2 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• GFNOrg / gfn-diffusion
  ☆34Updated 2 months ago
• J-zin / Awesome-Diffusion-Flow-Samplers
  Collecting research materials on neural samplers with diffusion/flow models
  ☆48Updated this week
• mlvlab / CoBO
  Official PyTorch Implementation for Advancing Bayesian Optimization via Learning Correlated Latent Space (CoBO)
  ☆12Updated last month
• GitGyun / multi_task_neural_processes
  [ICLR'22] Multi-Task Neural Processes
  ☆8Updated 2 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆32Updated 3 years ago
• sbyebss / variational_wgf
  [ICML2022] Variational Wasserstein gradient flow
  ☆22Updated 2 years ago
• vdeborto / cdsb
  ☆23Updated 2 years ago
• clear-nus / NCDSSM
  PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…
  ☆25Updated last year
• zdhNarsil / Diffusion-Generative-Flow-Samplers
  PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…
  ☆24Updated last year
• saleml / continuous-gfn
  ☆24Updated last year
• cyz-ai / neural-approx-ss-lfi
  Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models
  ☆19Updated 2 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 5 years ago
• cambridge-mlg / neural_diffusion_processes
  ☆13Updated last year
• FilippoMB / Total-variation-graph-neural-networks
  Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.
  ☆20Updated 2 months ago
• yuan-yin / CoDA
  Generalizing to New Physical Systems via Context-Informed Dynamics Model
  ☆24Updated last year
• chrvt / denoising-normalizing-flow
  ☆20Updated 2 years ago
• noamroze / moser_flow
  ☆17Updated 3 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆52Updated 10 months ago
• DenisBless / variational_sampling_methods
  [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".
  ☆34Updated 5 months ago