bremen79 / preciseLinks
Portfolio REgret for Confidence SEquences
☆20Updated 10 months ago
Alternatives and similar repositories for precise
Users that are interested in precise are comparing it to the libraries listed below
Sorting:
- Code for minimum-entropy coupling.☆32Updated last year
- ☆65Updated 10 months ago
- Because we don't want a jupyter notebook mess...☆61Updated 4 months ago
- A Python package for generating concise, high-quality summaries of a probability distribution☆53Updated last month
- Deep Networks Grok All the Time and Here is Why☆37Updated last year
- 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 Gradient Agreement Filtering, from Chaubard et al. of Stanford, but for single machine microbatches, in Pytorch☆25Updated 8 months ago
- Code for the paper "Function-Space Learning Rates"☆23Updated 4 months ago
- ☆27Updated 2 years ago
- Sparse and discrete interpretability tool for neural networks☆63Updated last year
- ☆60Updated 3 years ago
- Multi-framework implementation of Deep Kernel Shaping and Tailored Activation Transformations, which are methods that modify neural netwo…☆72Updated 3 months ago
- Official Implementation of the ICML 2023 paper: "Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally …☆74Updated 2 years ago
- Understanding how features learned by neural networks evolve throughout training☆39Updated 11 months ago
- Code for "Counterfactual Token Generation in Large Language Models", Arxiv 2024.☆29Updated 11 months ago
- ☆58Updated last year
- ☆28Updated last year
- Implementations of growing and pruning in neural networks☆22Updated 2 years ago
- Replicating and dissecting the git-re-basin project in one-click-replication Colabs☆35Updated 3 years ago
- Generative cellular automaton-like learning environments for RL.☆19Updated 8 months ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…☆25Updated 11 months ago
- ☆65Updated 6 months ago
- Code Release for "Broken Neural Scaling Laws" (BNSL) paper☆59Updated last year
- Implementation of a holodeck, written in Pytorch☆18Updated last year
- Source code for the paper "Positional Attention: Expressivity and Learnability of Algorithmic Computation"☆14Updated 4 months ago
- unofficial re-implementation of "Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets"☆79Updated 3 years ago
- Code for☆27Updated 9 months ago
- ☆150Updated last year
- Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation precondition…☆183Updated 2 weeks ago