Alternatives and similar repositories for Awesome-Riemannian-Optimization

Users that are interested in Awesome-Riemannian-Optimization are comparing it to the libraries listed below

• kwignb / NeuralTangentKernel-Papers
  Neural Tangent Kernel Papers
  ☆115Updated 6 months ago
• WeiHuang05 / Awesome_Large_Foundation_Model_Theory
  Welcome to the 'In Context Learning Theory' Reading Group
  ☆29Updated 9 months ago
• locuslab / edge-of-stability
  ☆70Updated 8 months ago
• WeiHuang05 / Awesome-Feature-Learning-in-Deep-Learning-Thoery
  Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for sch…
  ☆189Updated 7 months ago
• JunjieYang97 / stocBiO
  Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"
  ☆49Updated 3 years ago
• chengxiang / LinearTransformer
  Pytorch code for experiments on Linear Transformers
  ☆21Updated last year
• tding1 / Neural-Collapse
  [NeurIPS 2021] A Geometric Analysis of Neural Collapse with Unconstrained Features
  ☆58Updated 3 years ago
• kilianFatras / awesome-optimal-transport
  A list of awesome papers and cool resources on optimal transport and its applications in general! As you will notice, this list is curren…
  ☆229Updated 4 years ago
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆61Updated 2 years ago
• iutzeler / skwdro
  Distributionally robust machine learning with Pytorch and Scikit-learn wrappers
  ☆14Updated this week
• benchopt / benchmark_bilevel
  Benchmark for bi-level optimization solvers
  ☆48Updated 2 months ago
• changwxx / Awesome-Optimal-Transport-in-Deep-Learning
  a collection of AWESOME things about Optimal Transport in Deep Learning
  ☆294Updated last year
• hendrydong / NTK-and-MF-examples
  Visualization of mean field and neural tangent kernel regime
  ☆20Updated last year
• epfml / optML-pku
  summer school materials
  ☆44Updated 2 years ago
• aw31 / empirical-ntks
  Efficient empirical NTKs in PyTorch
  ☆22Updated 3 years ago
• cjyaras / deep-lora-transformers
  Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation (ICML'24 Oral)
  ☆13Updated last year
• ege-erdogan / awesome-weight-space-learning
  Awesome papers on weight-space learning
  ☆26Updated 2 months ago
• MaximeRobeyns / bayesian_lora
  Bayesian Low-Rank Adaptation for Large Language Models
  ☆35Updated last year
• zzp1012 / SAM-in-Late-Phase
  [ICLR 2025 Spotlight] Code release for "Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late In Training"
  ☆13Updated 5 months ago
• jongharyu / neural-svd
  ☆20Updated 10 months ago
• vis-opt-group / BLO
  Bi-level Optimization for Advanced Deep Learning
  ☆46Updated 3 years ago
• xie-lab-ml / deep-learning-dynamics-paper-list
  This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success o…
  ☆281Updated last year
• zyushun / hessian-spectrum
  Code for the paper: Why Transformers Need Adam: A Hessian Perspective
  ☆60Updated 4 months ago
• andyjm3 / SLTrain
  SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining (NeurIPS 2024)
  ☆32Updated 9 months ago
• pilancilab / Riemannian_Preconditioned_LoRA
  source code for paper "Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models"
  ☆30Updated last year
• AKuzina / defend_vae_mcmc
  Code repository of the paper "Alleviating Adversarial Attacks on Variational Autoencoders with MCMC" published at NeurIPS 2022. https://a…
  ☆10Updated 2 years ago
• gortizji / linearized-networks
  Source code of "What can linearized neural networks actually say about generalization?
  ☆20Updated 3 years ago
• ZIYU-DEEP / Awesome-Information-Bottleneck
  This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.
  ☆366Updated last year
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• mansheej / icl-task-diversity
  Code for the paper "Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression"
  ☆21Updated 2 years ago