The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

Python Implementation of MUVERA (Multi-Vector Retrieval via Fixed Dimensional Encodings)

Dockerized Elasticsearch on cluster

A python module implementing interfaces for various public tabular priors

Lightweight and educational reimplementation of TabPFN

Training HuggingFace models on EHR data

Repository for TabICL: A Tabular Foundation Model for In-Context Learning on Large Data

🧪Yet Another ICU Benchmark: a holistic framework for the standardization of clinical prediction model experiments. Provide custom datasets, cohorts, prediction tasks, endpoints, preprocessing, and …

Relevance Prediction in E-commerce Product Search

Training code for TabDPT: Scaling Tabular Foundation Models on Real Data

gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI

A comprehensive toolkit and benchmark for tabular data learning, featuring 35+ deep methods, more than 10 classical methods, and 300 diverse tabular datasets.

MCP Server for EMRs with FHIR

Connect to an EHR and make clinical data available via MCP

SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image

(ICLR 2025) TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling

100+ Fine-tuning Tutorial Notebooks on Google Colab, Kaggle and more.

Code repository for DBMI's EHR foundation model benchmarks.

Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

Code supplement for "Foundation models for electronic health records: representation dynamics and transferability"

A toolkit for developing foundation models using Electronic Health Record (EHR) data.

MedAgentSim: Self-Evolving Multi-Agent Simulations for Realistic Clinical Interactions, MICCAI 2025 (oral and early accepted)

Schema definitions and Python types for Medical Event Data Standard, a standard for medical event data such as EHR and claims data

A BERT-based framework for processing and analyzing Electronic Health Records (EHR) data. It provides an end-to-end pipeline for data preprocessing, model training, and clinical outcome prediction.