machinestein / GNOT
Pytorch implementation of "Neural Optimal Transport with General Cost Functionals" (ICLR 2024)
☆17Updated 7 months ago
Alternatives and similar repositories for GNOT:
Users that are interested in GNOT are comparing it to the libraries listed below
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆20Updated 7 months ago
- Pytorch implementation of "Light Schrödinger Bridge" (ICLR 2024)☆54Updated 8 months ago
- PyTorch implementation of "Light Unbalanced Optimal Transport" (NeurIPS 2024)☆18Updated 3 months ago
- PyTorch implementation of "Kernel Neural Optimal Transport" (ICLR 2023)☆25Updated last year
- Entropic Optimal Transport Benchmark (NeurIPS 2023).☆23Updated last year
- Light and Optimal Schrödinger Bridge Matching (ICML 2024) official PyTorch implementation☆38Updated 8 months ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆37Updated last year
- PyTorch implementation of "Extremal Domain Translation with Neural Optimal Transport" (NeurIPS 2023)☆19Updated 3 months ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆32Updated 2 years ago
- ☆16Updated 3 weeks ago
- A repo where I play with conditional flow approaches for learning time-varying vector-fields.☆18Updated 10 months ago
- Repository for "Generative Flow Networks as Entropy-Regularized RL" (AISTATS-2024, Oral)☆32Updated last year
- Official implementation of the paper "You Do Not Fully Utilize Transformer's Representation Capacity"☆28Updated 2 months ago
- ☆27Updated 3 weeks ago
- Pytorch implementation of DGflow (ICLR 2021).☆17Updated 4 years ago
- Code release for "Stochastic Optimal Control Matching"☆33Updated 8 months ago
- Official PyTorch implementation for the paper Star-Shaped Denoising Diffusion Probabilistic Models☆21Updated 4 months ago
- A Tutorial for Diffusion Models☆47Updated last year
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 2 years ago
- NeurIPS23 "Flow Factorized Representation Learning"☆35Updated 5 months ago
- ☆32Updated 10 months ago
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆53Updated 2 years ago
- [NeurIPS 2023] Formulating Discrete Probability Flow Through Optimal Transport☆20Updated last year
- Derivative-Free, Training-Free, Guidance in Diffusion Models☆13Updated 6 months ago
- Neural Diffusion Processes☆77Updated 8 months ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆40Updated 2 years ago
- The source code for the paper "Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization" (ICLR 2025)☆26Updated last month
- ☆28Updated 8 months ago
- [NeurIPS 2021] Manifold Topology Divergence: a Framework for Comparing Data Manifolds☆13Updated 3 years ago
- PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…☆24Updated last year