thudzj / NeuralEigenFunctionLinks
☆17Updated 3 years ago
Alternatives and similar repositories for NeuralEigenFunction
Users that are interested in NeuralEigenFunction are comparing it to the libraries listed below
Sorting:
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago
- Neural Diffusion Processes☆81Updated last year
- A python package providing a benchmark with various specified distribution shift patterns.☆58Updated last year
- ☆34Updated 2 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆92Updated 3 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 3 years ago
- ☆18Updated last year
- Pytorch implementation of neural processes and variants☆29Updated last year
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆86Updated last year
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- Official PyTorch implementation of NeuralSVD (ICML 2024)☆20Updated last year
- Bayesian Attention Modules☆35Updated 4 years ago
- Code for our paper "Generative Flow Networks for Discrete Probabilistic Modeling"☆84Updated 2 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆38Updated 3 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆17Updated last year
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆45Updated 3 years ago
- ☆44Updated 3 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆67Updated 2 years ago
- Gradient Estimation with Discrete Stein Operators (NeurIPS 2022)☆17Updated last year
- Experiments for Neural Flows paper☆99Updated 3 years ago
- ☆71Updated 11 months ago
- Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.☆41Updated last year
- ☆32Updated 2 years ago
- PyTorch implementation of LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS☆31Updated 5 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- Code for reproducing results in the sliced score matching paper (UAI 2019)☆147Updated 5 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 3 years ago
- Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…☆105Updated 3 years ago