Fernando Moreno-Pino

Assistant Professor in Machine Learning at @BristolUni. Research Associate at @Oxford_Man_Inst. Previously PostDoc at @UniofOxford and PhD at @uc3m.

[Gerardo Duran-Martin @grrddm]

Part I of a Bayesian’s take on (Kalman) filtering—without Bayes.

I will cover filtering and applications—from classical tracking problems to time-series forecasting, sequential learning for neural networks, and fully-online reinforcement learning

https://t.co/Lw0Rw1easp

[Fernando Moreno-Pino @fermorenp]

Work done at @UniofOxford - @Oxford_Man_Inst.

📊 Poster: https://t.co/V52U9YR8hk.

📄 Paper: https://t.co/k5657ZmNSV.

[Fernando Moreno-Pino @fermorenp]

🚀 Today at #NeurIPS2024!

Join us for our presentation on “Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures”.

🕚 Time: 11:00–14:00.
📍 Room #2006, East Exhibit Hall.

Discover how to train much more efficient (& continuous!) Transformers!

[Fernando Moreno-Pino @fermorenp]

🚀 Exciting news! Thrilled to share that our paper on Rough Transformers has been accepted at @NeurIPSConf !🧠

We’ve developed a method to make Transformers more efficient and resilient with temporal data using path signatures. Check it: https://t.co/2R367PuY8r 🙌

#NeurIPS2024

[Alvaro Arroyo @arroyo_alvr]

A little late, but happy to announce that our paper on Rough Transformers ⛰️ has been accepted at @NeurIPSConf!

We present a way to make Transformers for temporal data more efficient and robust to irregular sampling through path signatures!

Read on!

#neurips2024

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[Johannes Brandstetter @jo_brandstetter]

We introduce Geometry-Informed Neural Networks to train shape generative models
without any data (!!), combining learning under constraints, neural fields as a suitable representation, and generating diverse solutions to under-determined problems:
🖥️: https://t.co/qRbJ9SXuc0

[Ignacio Peis @IgnacioPeis]

📢 Exciting opportunity to work with an outstanding team of researchers! 📢

Feel free to reach out to us if you want to know more details about the ongoing projects!

[Gerardo Duran-Martin @grrddm]

Happy to share that our outlier-robust Kalman filter (WoLF 🐺) has been accepted to #ICML!
https://t.co/dfyaZ7F6kf

We propose a novel filtering algorithm that is provably robust and has similar computation cost to the KF.

Now, why care about robust filtering?

[Caglar Gulcehre @caglarml]

I am honored to announce that we will organize the "Next Generation of Sequence Modeling Architectures" workshop at ICML 2024 this year in Vienna. The workshop will take place on Friday, the 26th of July. The workshop page is: https://t.co/zJrb9Zv4Fl

[Jakob Foerster @j_foerst]

As the @icmlconf discussion period is ending please go back to the papers you are reviewing and reread the autor responses. Did they address your concerns? If so, update your score. If not, add a specific response, not "I decided to keep my score". Do justice to time and effort🙏

[Fernando Moreno-Pino @fermorenp]

It seems that combining emotion-based learning, affective computing, and a sprinkle of “Transformers’ magic” could be game-changing for numerous applications.

[Hume AI @hume_ai]

Meet Hume’s Empathic Voice Interface (EVI), the first conversational AI with emotional intelligence.

[Fernando Moreno-Pino @fermorenp]

It was a pleasure to hear Prof. @geoffreyhinton's insights on the future of AI and the direction researchers should take to address its potential risks

[University of Oxford @UniofOxford]

Yesterday, Oxford University hosted Prof @geoffreyhinton, the ‘Godfather of AI’, to deliver its annual Romanes Lecture at the Sheldonian Theatre.

Watch in full ⬇️ #OxfordAI
https://t.co/SX1nBH3ODL

[Fernando Moreno-Pino @fermorenp]

@SuarezlledoJ Derivar e implementar el forward y backward de un MLP sencillo es la mejor manera de entender fácilmente su funcionamiento (y ayuda a apreciar mucho más las facilidades que nos dan frameworks como Pytorch...)

[Laura Nicolás-Sáenz PhD @Laura_nicolass]

If you have ever felt frustrated or a little bit stupid when learning a new skill, come feel that with me while we learn how to use @QuPath. It's fine! It's normal! We can get through it together.

Will you join me?

https://t.co/1uwJRU2MYe

[Estibaliz Gómez de Mariscal, PhD @gomez_mariscal]

Huge congratulations to @Laura_nicolass and cosupervsors @ArrateMunoz @jpascau on her recently defended PhD👩‍🎓 🚀🥳a truly creative work merging registration🧩and colour theory🎨for #digitalpathology + #immunohistochemistry image analysis👩‍💻🧑‍⚕️The fun starts right with the title💍👑

[Fernando Moreno-Pino @fermorenp]

@javaloyML @UniofOxford @Oxford_Man_Inst Thanks, Adrián! Hope to see you soon!

[Fernando Moreno-Pino @fermorenp]

Great personal news! 🎉

After successfully defending my PhD thesis, I am starting a Postdoctoral Researcher position at the @UniofOxford within the @Oxford_Man_Inst. I will be working at the intersection of Deep Learning and Quantitative Finance!

See you all soon in Oxford! 🇬🇧

[Fernando Moreno-Pino @fermorenp]

@IgnacioPeis @jesfrellsen @DTU_Compute @DataScienceDK ¡Enhorabuena Peis! Ha sido un honor compartir el camino 😉

[Laura Nicolás-Sáenz PhD @Laura_nicolass]

It is finally published!:
ABANICCO: A New Color Space for Multi-Label Pixel Classification and Color Analysis
https://t.co/C3H32SCoWD

[Pablo Sánchez @ML_pablosm]

📰Excited to introduce our latest paper “Learnable Graph Convolutional Attention Networks”!

https://t.co/52Aw0hduvp

Joint work by the awesome team @javaloyML, @amitzeani, and @IValeraM.

🔎 Sidenote: Let's meet at #NeurIPS2022!

🧵 (1/n)

[Laura Nicolás-Sáenz PhD @Laura_nicolass]

We have brought ABANICCO to #SPAOM2022 @SPAOM5
Come and discuss all the possible applications of our automatic color analysis method!
📍poster 3