Alternatives and similar repositories for skwdro

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

• iamalexkorotin / Wasserstein2Barycenters
  PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)
  ☆24Updated 3 years ago
• jcperdomo / performative-prediction
  ☆32Updated 3 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated 2 years ago
• tml-epfl / sgd-sparse-features
  SGD with large step sizes learns sparse features [ICML 2023]
  ☆33Updated 2 years ago
• thudzj / ELLA
  Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
  ☆16Updated 3 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated 2 years ago
• ermongroup / HyperSPN
  PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
  ☆13Updated 4 years ago
• cbg-ethz / bmi
  Mutual information estimators and benchmark
  ☆53Updated last month
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• ykwon0407 / fast_dist_shapley
  Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)
  ☆22Updated 2 years ago
• opendataval / opendataval
  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
  ☆99Updated 8 months ago
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆69Updated 5 months ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆22Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆44Updated 4 months ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆86Updated last year
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆70Updated 11 months ago
• dh7401 / T-Cal
  ☆10Updated 3 years ago
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆61Updated 2 years ago
• locuslab / edge-of-stability
  ☆71Updated 10 months ago
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆37Updated 2 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
• gortizji / linearized-networks
  Source code of "What can linearized neural networks actually say about generalization?
  ☆20Updated 4 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆92Updated 3 years ago
• ykwon0407 / wdro_local_perturbation
  Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
  ☆21Updated 2 years ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• chengxiang / LinearTransformer
  Pytorch code for experiments on Linear Transformers
  ☆23Updated last year
• skolouri / TopoTrans
  TopoTrans: Optimal Transport meets Topological Data Analysis
  ☆14Updated 2 years ago
• lfochamon / csl
  csl: PyTorch-based Constrained Learning
  ☆12Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• Shen-Lab / Bayesian-L2O
  [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