Roberto Capobianco

Research Scientist / Assistant Professor in Artificial Intelligence, Machine Learning and Robot Learning

[Roberto Capobianco @webrot]

Curious what @OneMileataTime or @garyleff think — is breakage just part of the loyalty design, or a real user pain?

[Roberto Capobianco @webrot]

Do not miss it

[Alessio Ragno @spideralessio]

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

[Roberto Capobianco @webrot]

@elonmusk, would you mind sharing or backing?

[Leilani sigmoid.social/@leilani @leilanigilpin]

A nice write up on our XAI for DRL workshop at AAAI earlier this year with @larosabiagio @runnerdude97
@webrot @spideralessio @MProietti_

[Biagio La Rosa @larosabiagio]

Heading to #AAAI2024 in a few hours!! If anyone is around drop me a message on Whova and we can meet there! ps: visit our workshop in the quoted message!

[Leilani sigmoid.social/@leilani @leilanigilpin]

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!

[Biagio La Rosa @larosabiagio]

I and @leilanigilpin are going to present the poster of this work tomorrow morning (10:45am) at #NeurIPS2023 . Paper #1522. Come and chat together about it!

[Yann LeCun @ylecun]

Current LLMs are trained on text data that would take 20,000 years for a human to read.
And still, they haven't learned that if A is the same as B, then B is the same as A.
Humans get a lot smarter than that with comparatively little training data.
Even corvids, parrots, dogs, and octopuses get smarter than that very, very quickly, with only 2 billion neurons and a few trillion "parameters."

[Leilani sigmoid.social/@leilani @leilanigilpin]

We just extended the deadline to November 21st!

[Roberto Capobianco @webrot]

Come join our team for an exciting internship!

[Sony AI @SonyAI_global]

As our work in Game AI expands, so does our team. Sony AI is now hiring for a Reinforcement Learning Research Intern to join our global Game AI group. Join us in leveraging AI to develop new, enriching gaming experiences. https://t.co/cOujjJooc8

[Peter Stone @PeterStone_TX]

This should be a fun workshop. Thanks for organizing!

[Biagio La Rosa @larosabiagio]

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!

[Roberto Capobianco @webrot]

@larosabiagio @PeterStone_TX

[Biagio La Rosa @larosabiagio]

Amazing (informal) news: Our paper has been accepted at #NeurIPS2023 and our workshop has been accepted at #AAAI2024 . I will share more details in the next few days about both of them. Both XAI-based! I think it's a great way to end my PhD journey. >>

[Bojan Tunguz @tunguz]

AGI will be able to install CUDA correctly on the first try.

[Marco Angelini @Lynos79]

1/9 We are very happy to share that our new paper titled "State of the Art of Visual Analytics for Explainable Deep Learning" has just been published by Computer Graphics Forum.

Open Access paper: https://t.co/hh7ylcl2cw
Interactive explorable survey: https://t.co/21bb4NZgGL

[Jürgen Schmidhuber @SchmidhuberAI]

Train a weight matrix to encode the backpropagation learning algorithm itself. Run it on the neural net itself. Meta-learn to improve it! Generalizes to datasets outside of the meta-training distribution. v4 2022 with @LouisKirschAI https://t.co/zAZGZcYtmO

[Biagio La Rosa @larosabiagio]

I'm happy to announce that our paper 📄"A self-interpretable module for deep image classification on small data" has been published today in the Applied Intelligence Journal (https://t.co/kLtAOZW1gk). 1/6 >>

[The (Weekly) Sports Piece @SportsPiece]

Episode 4. The one with "Outracing champion Gran Turismo drivers with deep reinforcement learning" by @webrot @Florian_fuu @leilanigilpin @PeterStone_TX @heyitdeclan @csherstan @neonleonb @HKitano #GTSophy @SonyAI_global

🎙️🙌

https://t.co/WleE8PnqY9

👇📑

[Gabriel Peyré @gabrielpeyre]

Gradient descent/ascent can be inefficient to find saddle point (Nash equilibrium) for min-max games, because of spiralling behaviour. https://t.co/KKKGQ48yl0