Alternatives and similar repositories for NeuralEigenFunction:

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

• justkolesov / Wasserstein1Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).
  ☆20Updated 6 months ago
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆71Updated 2 years ago
• thudzj / ELLA
  Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
  ☆16Updated 2 years ago
• thjashin / rodeo
  Gradient Estimation with Discrete Stein Operators (NeurIPS 2022)
  ☆17Updated last year
• allenbai01 / transformers-as-statisticians
  ☆29Updated last year
• GFNOrg / gfn-diffusion
  ☆24Updated last week
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆26Updated 3 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆84Updated 2 years ago
• iamalexkorotin / Wasserstein2Barycenters
  PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)
  ☆23Updated 2 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆27Updated 8 months ago
• MingyuKim87 / NPwSA
  Official PyTorch implementation of NPwSA: "Neural Processes with Stochastic Attention: Paying more attention to the context dataset (ICLR…
  ☆10Updated 2 years ago
• hichamjanati / debiased-ot-barycenters
  ☆24Updated 3 years ago
• locuslab / edge-of-stability
  ☆65Updated 3 months ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• namkoong-lab / whyshift
  A python package providing a benchmark with various specified distribution shift patterns.
  ☆57Updated last year
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 4 years ago
• zhougroup / BAM
  Bayesian Attention Modules
  ☆35Updated 4 years ago
• PrincetonLIPS / MaM
  Official code for Generative Marginalization Models [ICML 2024] [SPGIM 2023 Workshop Oral]
  ☆22Updated 7 months ago
• automl / is_mamba_capable_of_icl
  ☆15Updated 11 months ago
• LJSthu / Kernelized-HRM
  The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".
  ☆12Updated 3 years ago
• ngushchin / EntropicOTBenchmark
  Entropic Optimal Transport Benchmark (NeurIPS 2023).
  ☆20Updated last year
• thuwzy / ZhuSuan-PyTorch
  An Elegant Library for Bayesian Deep Learning in PyTorch
  ☆25Updated 2 years ago
• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆44Updated 2 years ago
• pnnl / torchntk
  ☆27Updated 2 years ago
• rpatrik96 / ima-vae
  This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivale…
  ☆23Updated 11 months ago
• pilancilab / Riemannian_Preconditioned_LoRA
  source code for paper "Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models"
  ☆23Updated 9 months ago
• facebookresearch / SOC-matching
  Code release for "Stochastic Optimal Control Matching"
  ☆30Updated 7 months ago
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆58Updated last year
• cunningham-lab / igr
  ☆31Updated 4 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 3 years ago