Highlights
- Pro
Stars
Interactive Streamlit workbench for visualizing eyetracking-while-reading scanpaths, computing reading easures, and exporting figures and tabular data.
Python suite for neuroscience research across all modalities.
The agent that grows with you
AI reviewing paper drafts for improvement.
AI-powered citation search & paper review for Overleaf — Chrome extension. Think Google Scholar but inside Overleaf. Also works with OpenAI Prism, & Opera.
Hundreds of models & providers. One command to find what runs on your hardware.
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Python package for Zuna, an EEG foundation model for inference.
Easy Sweeps: A command-line utility for automating W&B sweep creation, launch, and GPU process management with ease.
A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP
PaperBanana: Automating Academic Illustration For AI Scientists
EyeBench: Predictive Modeling from Eye Movements in Reading
Algorithms for the automated correction of vertical drift in eye-tracking data
This repository contains the Potsdam Textbook Corpus (PoTeC) which is a natural reading eye-tracking corpus.
OneStop: A 360-Participant Eye Tracking Dataset with Different Reading Regimes
📊 A simple command-line utility for querying and monitoring GPU status
⏰ AI conference deadline countdowns
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
A python package for processing eye movement data
Machine learning metrics for distributed, scalable PyTorch applications.
Typed argument parser for Python
🎓 Academic portfolio that boosts citations. AI generates pages, you own as Markdown. BibTeX auto-import, Jupyter, LaTeX, slides, visual block editor — free to host forever. 学术主页，AI 生成，Markdown 拥有 👇
🧱 Describe your site, AI builds it, you own it as Markdown. Snap together Tailwind blocks like Lego — landing pages, blogs, portfolios, docs & more. No AI slop. Free to deploy anywhere 👇
A playbook for systematically maximizing the performance of deep learning models.
Multimodal model for text and tabular data with HuggingFace transformers as building block for text data