🎉 Our latest #NeurIPS paper "On Logic-based Self-Explainable Graph Neural Networks" is officially out: https://t.co/BUhaEiWshu
We introduce LogiX-GIN, a novel self-explainable graph neural network layer that can be directly converted into logic rules!
@XAI_Research#xai#gnns
🚀 Excited to share: “XAI-Guided Continual Learning: Rationale, Methods, and Future Directions”, w/ @spideralessio@webrot.
📖 https://t.co/3MbhKZvnkV
💬 We’d be happy to chat more about this exciting direction! Feel free to reach out!
More info in 🧵.
@XAI_Research
Excited to share that our paper, “Transparent Explainable Logic Layers,” co-authored with @MarcPlantevit, Celine Robardet, and @webrot, will be presented at ECAI24! 🧠📊
Check it out! 📑 https://t.co/FDcE5GybWQ
#XAI#ECAI2024
Heading to #AAAI2024 today with @runnerdude97 to meet up with @larosabiagio and others for the XAI for DRL workshop: https://t.co/8BWfzgwIec. Let me know if you're around!
Please RT! Two weeks left to submit your work to our workshop on #eXplainableAI approaches for Deep #ReinforcementLearning#AAAI24, Vancouver (https://t.co/a5F8Krczpg) Deadline: Nov 15!
Please RT! Opened the call for papers for our workshop on #eXplainableAI approaches for Deep #ReinforcementLearning#AAAI24, Vancouver
(https://t.co/a5F8Krc1zI)
Deadline: Nov 15!
The main focus is on #XAI methods for interpreting deep #RL models but every #XAI paper is welcome!
Purtroppo anche oggi dobbiamo prenderci una pausa da Breaking Italy, scusateci!
Però c'è sempre Grandi Linee che vi racconta cosa succede oggi! 🎙❤️
https://t.co/BEvCpFBOpz