Popular GitHub Repositories for Complexity Measure

Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

Python package for easily interfacing with chat apps, with robust features and minimal code complexity.

Transformer based on a variant of attention that is linear complexity in respect to sequence length

Fast underwater image enhancement for Improved Visual Perception. #TensorFlow #PyTorch #RAL2020

If you can measure it, consider it predicted

[NeurIPS 2021 Spotlight] & [IJCV 2024] SOFT: Softmax-free Transformer with Linear Complexity

This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms

?FFPA(Split-D): Yet another Faster Flash Prefill Attention with O(1) GPU SRAM complexity for headdim > 256, ~2x↑?vs SDPA EA.

Low-complexity neural image & video codec.

Training-free Post-training Efficient Sub-quadratic Complexity Attention. Implemented with OpenAI Triton.

Identify bias and measure fairness of your data

Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)

[ICLR 2022] "As-ViT: Auto-scaling Vision Transformers without Training" by Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou

Word2Vec based similarity measure of mass spectrometry data.

Simulate collaborative ML scenarios, experiment multi-partner learning approaches and measure respective contributions of different datasets to model performance.

Measure the sentiment towards a word, name or sentence on social networks

Source code of the Paper "Diffusion-Based Generative Prior for Low-Complexity MIMO Channel Estimation"

AI-powered code quality analysis using MCP to help AI assistants review code more effectively. Analyze git changes for complexity, security issues, and more through structured prompts.