Turning Tabular Foundation Models into Graph Foundation Models

GraphPFN: A Prior-Data Fitted Graph Foundation Model

GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data

⚡ TabPFN: Foundation Model for Tabular Data ⚡

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

Research on Tabular Deep Learning: Papers & Packages

A benchmark of meaningful graph datasets with tabular node features

(ICLR 2025 Spotlight) TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Open Machine Learning Course

Noise-Contrastive Visualization

Lo-Hi Splitter for Modern Splits of Molecular Datasets

(NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning

The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"

Topological Deep Learning

Graph Neural Network Library for PyTorch

Python package built to ease deep learning on graph, on top of existing DL frameworks.

A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?

A set of exercises for deliberate Git Practice

Vim exercises based on the book - Practical Vim.

Practical assignments of the Deep|Bayes summer school 2019

NYU Deep Learning Spring 2020

Машинное обучение на ФКН ВШЭ