Lightweight, useful implementation of conformal prediction on real data.

[Nature Machine Intelligence 2025] Emulating Human-like Adaptive Vision for Efficient and Flexible Machine Visual Perception

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports comp…

[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"

TopicGPT: A Prompt-Based Framework for Topic Modeling [NAACL'24]

Conformal Prediction for Time Series with Modern Hopfield Networks

Healthcare and biomedical datasets, for AI/ML

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).

PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation

A high-throughput and memory-efficient inference and serving engine for LLMs

Open source tools for computational pathology - Nature BME

Multimodal Whole Slide Foundation Model for Pathology - Nature Medicine

Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes

🧱 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 👇

source code for ICLR'22 paper "VOS: Learning What You Don’t Know by Virtual Outlier Synthesis"

Deploy twikoo to Zeabur or Railway

Apache ECharts is a powerful, interactive charting and data visualization library for browser

Clinical Histopathology Imaging Evaluation Foundation Model

High-quality implementations of standard and SOTA methods on a variety of tasks.

Kaggle DataSet - Give Me Some Credit

A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

A simple and effective method for detecting out-of-distribution images in neural networks.