RylanSchaeffer / Stanford-AI-Alignment-Double-Descent-Tutorial

Related projects ⓘ

Alternatives and complementary repositories for Stanford-AI-Alignment-Double-Descent-Tutorial

• bilal-chughtai / rep-theory-mech-interp
  ☆24Updated last year
• srush / drop7
  ☆18Updated 6 months ago
• MilesCranmer / pysr_scaling_laws
  You should use PySR to find scaling laws. Here's an example.
  ☆31Updated last year
• rmascarenhas / foppl
  First-Order Probabilistic Programming Language
  ☆26Updated 5 years ago
• EleutherAI / mdl
  Minimum Description Length probing for neural network representations
  ☆16Updated 2 weeks ago
• smonsays / jax-hypernetwork
  A simple hypernetwork implementation in jax using haiku.
  ☆23Updated 2 years ago
• alexzhang13 / Triton-Puzzles-Solutions
  Personal solutions to the Triton Puzzles
  ☆16Updated 3 months ago
• KhoomeiK / complexity-scaling
  gzip Predicts Data-dependent Scaling Laws
  ☆32Updated 5 months ago
• cgarciae / einop
  ☆58Updated 2 years ago
• COR-OPT / SuperPolyak.py
  Pytorch implementation of SuperPolyak subgradient method.
  ☆43Updated last year
• JoshEngels / SAE-Dark-Matter
  Code for our paper "Decomposing The Dark Matter of Sparse Autoencoders"
  ☆14Updated 3 weeks ago
• EleutherAI / features-across-time
  Understanding how features learned by neural networks evolve throughout training
  ☆31Updated 3 weeks ago
• IBM / abductive-rule-learner-with-context-awareness
  PyTorch Implementation of the paper "Towards Learning Abductive Reasoning using VSA Distributed Representations".
  ☆12Updated 2 months ago
• IDSIA / neuraldiffeq-fwp
  Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…
  ☆18Updated 2 years ago
• Artur-Galstyan / statedict2pytree
  ☆40Updated 4 months ago
• andrew-silva / clean-rl-mlx
  Clean RL implementation using MLX
  ☆26Updated 8 months ago
• ssokota / mec
  Code for minimum-entropy coupling.
  ☆29Updated 4 months ago
• Rose-STL-Lab / AutoSTPP
  Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…
  ☆24Updated 3 weeks ago
• amudide / switch_sae
  Efficient Dictionary Learning with Switch Sparse Autoencoders (SAEs)
  ☆13Updated last month
• ethz-spylab / superhuman-ai-consistency
  ☆28Updated last year
• bazingagin / npc_lv
  ☆8Updated last year
• random-matrix-learning / slides
  LaTeX source code for the slides
  ☆21Updated 3 years ago
• Ping-C / optimizer
  This repository includes code to reproduce the tables in "Loss Landscapes are All You Need: Neural Network Generalization Can Be Explaine…
  ☆34Updated last year
• tangle-software / tangles
  Tangle Software Library
  ☆23Updated 6 months ago
• crowsonkb / dice-mc
  DiCE: The Infinitely Differentiable Monte-Carlo Estimator
  ☆30Updated last year
• catid / spectral_ssm
  Implementation of Spectral State Space Models
  ☆17Updated 8 months ago
• Silent-Zebra / twisted-smc-lm
  ☆22Updated this week
• thestephencasper / everything-you-need
  we got you bro
  ☆32Updated 3 months ago
• rougier / numpy-glm
  GL Mathematics for Numpy
  ☆21Updated 7 months ago
• SuReLI / NeurOps
  Implementations of growing and pruning in neural networks
  ☆21Updated last year