SysON: web-based graphical modelers for SysMLv2. Please visit https://mbse-syson.org and contact Obeo https://www.obeosoft.com/en/contact for more details!

Code and Data for EMNLP2020 Paper "KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation"

Code for "Text Generation from Knowledge Graphs with Graph Transformers"

Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs (authors' implementation for the TACL20 paper)

Additional tools for Visual Effect Artists

Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs" (KDD 2021).

[ICCV 2019] Monocular depth estimation from a single image

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips

[NeurIPS 2022] DRAGON 🐲: Deep Bidirectional Language-Knowledge Graph Pretraining

Framework to train and simulate a spiking neural network (SNN) using Brian2, that implements a learning rule that combines STDP with a global feedback mechanism to support strong, contrasty pattern…

Python script to stream EEG data from the muse 2016 headset

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

EEG Experiments in Python

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

Graph neural networks for molecular design.

Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models"

Codes for our paper "JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs" (ACL 2021 Findings)

Complete collection of my PGF/TikZ figures.

GAIA, with the full name Generic AIOps Atlas, is an overall dataset for analyzing operation problems such as anomaly detection, log analysis, fault localization, etc.

Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco Pavone.

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

📈 Awesome resources related to GNNs for Time Series Analysis (GNN4TS) 🔥 https://arxiv.org/abs/2307.03759