emanuele / DSPFP
This is a Python implementation of the Doubly Stochastic Projected Fixed Point (DSPFP) algorithm for solving the Quadratic Assignment Problem / Graph Matching..
☆9Updated 5 years ago
Alternatives and similar repositories for DSPFP:
Users that are interested in DSPFP are comparing it to the libraries listed below
- ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.☆16Updated 7 months ago
- ☆17Updated last year
- Python implementation of the supervised graph prediction method proposed in http://arxiv.org/abs/2202.03813 using PyTorch library and POT…☆13Updated 3 years ago
- ☆17Updated last year
- The official implementation of Convergent Graph Solvers (CGS)☆21Updated 3 years ago
- Code for "Maximizing Acquisition Functions for Bayesian Optimization"☆13Updated 6 years ago
- Manifold Learning by Mixture Models of VAEs for Inverse Problems☆17Updated 6 months ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆20Updated 6 months ago
- Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning☆21Updated last year
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆13Updated 2 years ago
- ☆11Updated last year
- Tensorflow implementation for the SVGP-VAE model.☆22Updated 3 years ago
- Official PyTorch implementation of NPwSA: "Neural Processes with Stochastic Attention: Paying more attention to the context dataset (ICLR…☆10Updated 2 years ago
- This is the code related to the article 'Intrinsic persistent homology via density-based metric learning'☆10Updated last year
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 2 years ago
- Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"☆22Updated 4 years ago
- [NeurIPS 2019] LOIS: Learning to Optimize In Swarms, guided by posterior estimation☆18Updated 3 years ago
- Code for "Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation" @ NeurIPS 2023☆13Updated last year
- ☆28Updated 7 months ago
- Python implementation for Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces.☆13Updated 3 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 4 years ago
- Differentiable Euler Characteristic Transform☆17Updated 9 months ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆51Updated 3 years ago
- Mini Bayesian Optimization package for ACML2020 Tutorial on Bayesian Optimization☆15Updated 2 years ago
- Graph matching and clustering by comparing heat kernels via optimal transport.☆26Updated 2 years ago
- ☆12Updated 8 months ago
- ☆9Updated last year
- Accompanying code for AAAI 2021 publication - High-Dimensional Bayesian Optimization via Tree-Structured Additive Models☆11Updated 9 months ago