Alternatives and similar repositories for trumpets

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

• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆33Updated 3 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆55Updated 11 months ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆103Updated last year
• vdeborto / cdsb
  ☆23Updated 3 years ago
• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆16Updated 8 months ago
• vislearn / HINT
  Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".
  ☆21Updated 4 years ago
• CACTuS-AI / GlowIP
  Code to reproduce results from "Invertible generative models for inverse problems: mitigating representation error and dataset bias"
  ☆21Updated 5 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 2 years ago
• chenlin9 / Gaussianization_Flows
  ☆21Updated 5 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆48Updated last week
• iamalexkorotin / Wasserstein2Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)
  ☆42Updated 3 years ago
• sbyebss / variational_wgf
  [ICML2022] Variational Wasserstein gradient flow
  ☆23Updated 2 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 3 years ago
• CW-Huang / sdeflow-light
  A minimalist implementation of score-based diffusion model
  ☆127Updated 3 years ago
• kkothari93 / fionet
  Official repo for "Learning the geometry of wave-based imaging"
  ☆12Updated 4 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆78Updated 3 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 4 years ago
• locuslab / orthogonal-convolutions
  Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness
  ☆47Updated 4 years ago
• 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
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆22Updated 4 years ago
• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆81Updated 11 months ago
• TimRoith / BregmanLearning
  Optimizing neural networks via an inverse scale space flow.
  ☆16Updated last year
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 5 years ago
• chrvt / denoising-normalizing-flow
  ☆20Updated 2 years ago
• AaltoML / PeriodicBNN
  Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)
  ☆19Updated 3 years ago
• Sulam-Group / k-rcps
  "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"
  ☆17Updated last month
• lucadellalib / bayestorch
  Lightweight Bayesian deep learning library for fast prototyping based on PyTorch
  ☆13Updated 2 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆20Updated 3 years ago