Code for the ALiBi method for transformer language models (ICLR 2022)

The simplest, fastest repository for training/finetuning medium-sized GPTs.

Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).

Python implementation of the Latent Space Hawkes (LSH) model for continuous-time dynamic networks

Collection of papers on state-space models

Annotated version of the Mamba paper

Pytorch implementation of Simplified Structured State-Spaces for Sequence Modeling (S5)

Liquid Structural State-Space Models

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

EasyTPP: Towards Open Benchmarking Temporal Point Processes

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Code for Transformer Hawkes Process, ICML 2020.

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Implementation of "Neural Jump-Diffusion Temporal Point Processes" (ICML 2024 Spotlight)

Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.

An Empirical Evaluation of Temporal Graph Benchmark

Temporal Graph Benchmark project repo

A Library for Dynamic Graph Learning (NeurIPS 2023)

Curated list of data science interview questions and answers

All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.

Must-read papers on graph foundation models (GFMs)

Papers about large graph models.

Learning from positive and unlabeled data with a selection bias (nnPUSB) reproductive code on MNIST and CIFAR10

Pytorch implementation of risk estimators for unbiased and non-negative positive-unlabeled learning

Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data