Alternatives and similar repositories for active-surrogate-estimators:

Users that are interested in active-surrogate-estimators are comparing it to the libraries listed below

• MadryLab / modeldiff
  ModelDiff: A Framework for Comparing Learning Algorithms
  ☆56Updated last year
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆19Updated 2 years ago
• rtaori / data_feedback
  Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"
  ☆15Updated 2 years ago
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆46Updated 2 years ago
• JonasGeiping / dataaugs
  ☆17Updated 2 years ago
• UW-Madison-Lee-Lab / Expressive_Power_of_LoRA
  Code for "The Expressive Power of Low-Rank Adaptation".
  ☆20Updated 11 months ago
• pomonam / jax-influence
  A simple Jax implementation of influence functions.
  ☆16Updated 11 months ago
• MadryLab / datamodels
  ☆28Updated last year
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• formll / resolving-scaling-law-discrepancies
  ☆18Updated 8 months ago
• RandallBalestriero / SplineLLM
  ☆15Updated last year
• nick11roberts / XD
  ☆11Updated 2 years ago
• allenbai01 / transformers-as-statisticians
  ☆31Updated last year
• Bradley-Butcher / Conformers
  Unofficial implementation of Conformal Language Modeling by Quach et al
  ☆28Updated last year
• facebookresearch / ModelRatatouille
  Recycling diverse models
  ☆44Updated 2 years ago
• AndyShih12 / LongHorizonTemperatureScaling
  PyTorch implementation for "Long Horizon Temperature Scaling", ICML 2023
  ☆20Updated last year
• JeanKaddour / NoTrainNoGain
  Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)
  ☆79Updated last year
• BrachioLab / incontext_influences
  In-context Example Selection with Influences
  ☆15Updated last year
• felixzli / synthetic_pretraining
  ☆39Updated 2 years ago
• rmwu / sea-reproduce
  Sample, estimate, aggregate: A recipe for causal discovery foundation models
  ☆10Updated 9 months ago
• ethz-spylab / superhuman-ai-consistency
  ☆28Updated last year
• tml-epfl / sgd-sparse-features
  SGD with large step sizes learns sparse features [ICML 2023]
  ☆32Updated last year
• gortizji / linearized-networks
  Source code of "What can linearized neural networks actually say about generalization?
  ☆20Updated 3 years ago
• shoaibahmed / metadata_archaeology
  Official code for the paper: "Metadata Archaeology"
  ☆19Updated last year
• MadryLab / pretraining-distribution-shift-robustness
  ☆14Updated last year
• Yujun-Yan / Neural-Execution-Engines
  Code for Neural Execution Engines: Learning to Execute Subroutines
  ☆17Updated 4 years ago
• NingMiao / InstaAug
  ☆13Updated 2 years ago
• p-lambda / in-n-out
  Code for the ICLR 2021 Paper "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"
  ☆12Updated 3 years ago
• ml-jku / quam
  Quantification of Uncertainty with Adversarial Models
  ☆28Updated last year
• arnab-api / romba
  Applies ROME and MEMIT on Mamba-S4 models
  ☆14Updated 11 months ago