New work with Tuan Minh Pham (@physicsidea) and Fernando Metz (@FernandoL2006)!
"Effects of clustering heterogeneity on the spectral density of sparse networks"
https://t.co/8sgbVG8GFG
XI WPSM – Workshop on Probabilistic and Statistical Methods. 25–27 Feb 2026 @ufscaroficial – São Carlos/SP
🔹 7 plenary talks
🔹 2 mini-conferences
🔹 Minicourse: Neural Nets with PyTorch
🔹 Special sessions on Complex Networks & Probability
🔗 https://t.co/UtspvDOHoO
If you’re working in Network Dynamics and interested in Power Grids or Climate Science, I’d be happy to host you for a postdoc at Kadir Has University @khasedutr, Istanbul via the 2236-A CoCirculation3 call funded by @Tubitak & @HorizonEU MSCA-COFUND!
Details in next post!
Together with @notalbertalonso and Karel Proesmans, we show how irreversible a neural network is in terms of its dissipation rate and how optimal information processing at the edge of chaos is related to this robust energy expenditure https://t.co/c3JbcjSF2v
Now out: "A machine learning approach to predicting dynamical observables from network structure" (https://t.co/kmmsSvGeDd). Here we use ML techniques to predict dynamic outcomes of networked systems using their structural properties. Kudos to @FranciscoICMC@thomas_peron et al.
Proud to share my work on DMFT for dynamical systems on complex networks, selected as an Editors'Suggestion in PRL! @CompSysSoc@ifufrgs
The paper presents a general solution for models of complex systems on sparse and directed networks. Check it out:
https://t.co/fh90HC0YWO
🕮 New Book Release! 😀
Happy to share my new book, Machine Learning Beyond Point Predictions: Uncertainty Quantification.
Tools to tackle aleatoric & epistemic uncertainties in AI. +
"Statistical Laws in Complex Systems: Combining Mechanistic Models and Data Analysis", my 150p monograph written at @SydneyMaths and @mpi_pks is now published by @SpringerNature:
Electronic/print: https://t.co/Il47TpLEFJ
ask me for e-copies or https://t.co/Qm4m3guJvX
A thread:
New work with Tuan Minh Pham (@physicsidea) and Fernando Metz (@FernandoL2006)!
"Effects of clustering heterogeneity on the spectral density of sparse networks"
https://t.co/8sgbVG8GFG
We are releasing DOCES (Dynamical Opinion Clusters Exploration Suite), a new Python library for studying opinion dynamics. Designed to simulate social network interactions, it allows you to model different features of social networks. Check it out at https://t.co/1T3oqVyPAk
Our paper https://t.co/romNSydcKG with 2 perspective: evolutionary biology, phenotypic robustness emerging from dynamic genotype-phenotype map; Hopfield-networks: the network tries to retrieve dynamic patterns that in turn shaped by the network structure in the previous iteration
#PhysCon2024 - The program and social events are now live at https://t.co/s4YUktz4iN. Unforgettable scientific and social moments are on the way! It’s not too late to grab your spot! The basin of attraction is attached from our university museum! @khasedutr@nodds_lab
Our paper "Regression Trees for Fast and Adaptive Prediction Intervals," co-authored with @kuben45, @mpotto1 and @rbstern, is now published in Information Sciences! 🎉
We introduce Locart and Loforest to calibrate prediction intervals for regression with coverage guarantees. +
My first preprint as a solo-author is out and public on the ArXiV!! https://t.co/ZE631Havew 🥳
Here I develop a new method to deal with stochastic coupled oscillators, allowing one to easily obtain any fluctuations and finite-size effects, even analytically!
Thread! 🧵
Our review "Contagion dynamics on higher-order networks" is out in @NatRevPhys (https://t.co/s3CjIONYia). We review the literature on the topic and take the opportunity to propose a unified formalism covering most of the functional forms used for the spreading dynamics (1/2).
It was great to have dinner with my Brazilian friend in São Paulo this evening, learning all about life in Brazil and discussing future work together. Thank you @thomas_peron 🇧🇷