aks2203 / easy-to-hardLinks
Official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"
☆59Updated 3 years ago
Alternatives and similar repositories for easy-to-hard
Users that are interested in easy-to-hard are comparing it to the libraries listed below
Sorting:
- Meta-learning inductive biases in the form of useful conserved quantities.☆37Updated 2 years ago
- Code accompanying our paper "Feature Learning in Infinite-Width Neural Networks" (https://arxiv.org/abs/2011.14522)☆63Updated 4 years ago
- Code Release for "Broken Neural Scaling Laws" (BNSL) paper☆59Updated last year
- ☆192Updated 4 months ago
- Differentiable Algorithms and Algorithmic Supervision.☆116Updated 2 years ago
- Multi-framework implementation of Deep Kernel Shaping and Tailored Activation Transformations, which are methods that modify neural netwo…☆74Updated 3 months ago
- Neural Turing Machines in pytorch☆48Updated 3 years ago
- Code for minimum-entropy coupling.☆32Updated last year
- Usable implementation of Emerging Symbol Binding Network (ESBN), in Pytorch☆25Updated 4 years ago
- This repository includes code to reproduce the tables in "Loss Landscapes are All You Need: Neural Network Generalization Can Be Explaine…☆40Updated 2 years ago
- Implementation of deep implicit attention in PyTorch☆65Updated 4 years ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆59Updated 2 years ago
- ☆52Updated last year
- A case study of efficient training of large language models using commodity hardware.☆68Updated 3 years ago
- JAX implementation of "Fine-Tuning Language Models with Just Forward Passes"☆19Updated 2 years ago
- minGPT in JAX☆48Updated 3 years ago
- The Energy Transformer block, in JAX☆58Updated last year
- Replicating and dissecting the git-re-basin project in one-click-replication Colabs