Interdisciplinary Physics Team (InPhyT)
@In_Phy_T
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Complex Systems Modelling Group | Computational #SocialScience📱, #Epidemiology 🦠 , #Neuroscience 🧠, #ML #GNN 🤖| #JuliaLang #Python 🧑💻.
Italy
Joined October 2020
📢 We're happy to announce the new release of MultilayerGraphs.jl (v1.1) 🎉!. Interested in multilayer network science in @JuliaLanguage?. Read the following 🧵summarising the main features of the package by @Claudio__Moroni and @PietroMonticone. (1/13).
github.com
A Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. - JuliaGraphs/MultilayerGraphs.jl
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RT @PietroMonticone: A very nice article in @QuantaMagazine mentions our #EquationalTheories project, led by Terence Tao, which aims to adv….
quantamagazine.org
Mathematicians have started to prepare for a profound shift in what it means to do mathematics.
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RT @PietroMonticone: Glad for the opportunity to collaborate with @emilyriehl in setting up the blueprint infrastructure for this new colla….
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RT @Jose_A_Alonso: Getting started with Blueprint-Driven formalization projects in Lean. ~ Pietro Monticone (@PietroMonticone). https://t.c….
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RT @PietroMonticone: My colleagues and I have almost finished the formalisation of Fermat’s Last Theorem for exponent 3 in @leanprover. W….
github.com
Proof in Lean of Fermat Last Theorem for exponent 3 - riccardobrasca/flt3
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RT @net_science: Multilayer Network Science: from Cells to Societies. (arXiv:2401.04589v1 [physics.soc-ph])
arxiv.org
Networks are convenient mathematical models to represent the structure of complex systems, from cells to societies. In the past decade, multilayer network science -- the branch of the field...
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RT @Claudio__Moroni: Check out the Pytorch Geometric (@PyG_Team) implementation of the "Gravity-Inspired Graph Autoencoders for Directed Li….
github.com
Pytorch Geometric implementation of the "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" paper. - ClaudMor/gravity_gae_torch_geometric
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RT @Claudio__Moroni: Thanks @mljclub and @unito for the opportunity to give this presentation about Graph Deep Learning. We introduced #….
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RT @Claudio__Moroni: MultilayerGraphs.jl allows for flexible and user-friendly construction of (general) multilayer graphs while retaining….
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📢Finally out the #JuliaCon 2023 talk “MultilayerGraphs.jl: Multilayer Network Science in Julia” presented by @PietroMonticone and @Claudio__Moroni at @MIT @MIT_CSAIL!. 🌐 Website 📹 Video 📑 Slides
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RT @PietroMonticone: Very glad to have attended the 2nd edition of the summer school in #GeometricAnalysis organized by the mathematics dep….
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RT @Claudio__Moroni: Last week I completed the #IPSP2023 initiative organized by the Physics Department of @UniTrento , @ConfindustriaTN ,….
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RT @PietroMonticone: @cameron_pfiffer Hi Cameron, here are a few introductory resources I'd recommend to read / watch: . 📖@JuliaLanguage ht….
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RT @PietroMonticone: @cameron_pfiffer @JuliaLanguage @MITCompThinking @PlutoJL @OfficialLoganK @3blue1brown @juliacon @MIT @MITMath @giomda….
youtube.com
This short course on Julia and open-source development is aimed at helping "intermediate" coders become participants in the world of open-source software dev...
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RT @ComuneLab: Latest from the lab: . “More is different in real-world multilayer networks”. just appeared in @NaturePhysics !. Curious abo….
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RT @Claudio__Moroni: Useful paper from @Abel0828, @jure, @PanLi90769257 et al. on representation learning of temporal graphs via Causal An….
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RT @Claudio__Moroni: A very interesting paper by Lutz Oettershagen, @nmkriege, @chrsmrrs and Petra Mutzel on static representations of temp….
epubs.siam.org
Abstract Many real-world graphs are temporal, e.g., in a social network persons only interact at specific points in time. This temporality directs possible dissemination processes on the graph, such...
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