Giovanni Maffei

Neuroscientist, AI Research Scientist, analogue synthesizer

[Diogo Santos-Pata @DiogoSantosPata]

Really happy to see it coming to light. It turns out theta entrains deepMEC neurons to CA1 cell assemblies while navigating for later synchronization during rest replay. How cool is that?
Hats off to @FOlafsdottir & @caswellcaswell, learned an insane amount during the making.

[Klaudia Grechuta, PhD @GrechutaKlaudia]

What determines body boundaries? Do they exist?

By manipulating #perception in a #VR study, we found that #embodiment depends not only on sensorimotor contingencies but also on the congruency of the surrounding environment

👉 https://t.co/UVSy3l3kvl

@SPECS_lab @IBECBarcelona

[Causality ALGO @CausalityA]

What is better than Machine Learning? 🥁
DOUBLE Machine Learning 😍

#borjaVelascoRegúlez explains what Double Machine Learning is in a very good article 👌🏼

#CausalInference #AI #MachineLearning

https://t.co/w4pypbIRBn

[Michael Wooldridge @wooldridgemike]

Some great lectures on AI and ML from Oxford University. A thread... [1/32] @CompSciOxford @UniofOxford

[Giovanni Maffei @GioMaffei]

congrats to all the colleagues that contributed to this work @zucca_bcn Jordi Ysard Puigbò @DiogoSantosPata Marco Galli Adrià Tauste Campo @Dr_Rocamora @PaulVerschure

[Giovanni Maffei @GioMaffei]

Our new preprint is out! We show that within human frontal cortical networks, theta oscillations could encode a control signal that promotes the execution of deliberate actions. A collaboration between @SPECS_lab @IBECBarcelona @imimat and @cbcUPF https://t.co/7c9h8n8WaM

[Clément Moulin-Frier @ClemMoulinFrier]

Next week we organize the SMILES workshop (Sensorimotor Interaction, Language and Embodiment of Symbols) as a satellite of @ICDL_EpiRob. Fully virtual, 6 keynote speakers and a number of paper presentations. Checkout the program and register for free at https://t.co/33HihKmxml

[Bradley Love @ProfData]

One upshot is that there are no value areas per se in the brain because wherever there is value there is also a confidence signal that combines to provide a post decision evaluation of the choice option.

[Chip Huyen @chipro]

Some resources that I’ve found really helpful to understand machine learning in production.

1. Engineering starts with infrastructure. @vtuulos gave a great overview of the relationship between data science and infrastructure at Netflix

https://t.co/BrVrrG5HC0

[Reza Shadmehr @reziliusReza]

From a machine learning perspective, there is something quite odd about the cerebellum: the error information about the activities of the output layer neurons are sent strongly to the middle layer neurons (Purkinje cells), but not to the output layer neurons.
Why?

[Aran Komatsuzaki @arankomatsuzaki]

My first blog post was released 🥳

I have aggregated ~20 notable recent ML papers, esp. from ICLR 2021, with summaries, visualizations and my comments!

The development in each field is summarized, and the future trends are speculated.

https://t.co/E8mGrGHoIB

[MIT Technology Review @techreview]

Op-ed: Too much research applying machine learning to real-world problems is marginalized in the AI community. This is preventing AI from living up to its promise of solving the world's biggest problems.
https://t.co/4uHRzHQZwX

[Danilo Bzdok @danilobzdok]

Does #significance coincide with successful #prediction in #biomedicine? Our latest paper:

https://t.co/6m95ORldB9

combining massive empirical data simulations and real-world clinical datasets. Joint work with @dngman @BertrandThirion
Thread:👇🏽👇🏿👇 -viz powered by @matplotlib

[Papers with Code @paperswithcode]

🎉 Papers with Code partners with arXiv! Code links are now shown on arXiv articles, and authors can submit code through arXiv. Read more: https://t.co/kO6zhWAWGH

[Santiago @svpino]

Python 3.9 🐍 is out! 🥳

Here are the 5 new features you care about.

🧵👇

[Sindy Löwe @sindy_loewe]

[1/3] Very excited to announce our @NeurIPSConf workshop Beyond Backpropagation - Novel Ideas for Training Neural Architectures!

Website & call for papers: https://t.co/J0hQgXKaHX
(by 9th Oct)

Submit your short papers and join for great discussions on alternatives to backprop!

[Alfredo Canziani @alfcnz]

Week ⑭ videos 🎥 are up! 🎉

Lecture: https://t.co/kNh7yoXnka
Practicum: https://t.co/tu77YgjRkw
Transcript: https://t.co/rSN6NBmaRT

Learn about:
• structured prediction with energy-based factor graph;
• graph transformer net;
• Viterbi algo;
• Lagrangian backprop;
…

[Nick Pawlowski @pwnic]

Our new work on deep structural causal models combines VI + NFs to tractably generate convincing counterfactuals on high-dimensional data, e.g. brain images, fulfilling all 3 levels of @yudapearl's causation ladder:
https://t.co/vKcMzwwj7C

[Klaudia Grechuta, PhD @GrechutaKlaudia]

Here goes our new study https://t.co/NBLrHG0Hdp which assesses the impact of #COVID19 on affective states. Using a scalable method and #MachineLearning, we found that #Quarantine and #lockdown have a significant impact on mental #Wellbeing
@HectorCarral @SPECS_lab @IBECBarcelona