Media Summary: Speaker: Spyros Chatzivasileiadis (DTU) Session: DTU Workshop on "Learning and Optimization for Decision-Making Under ... In this AI Research Roundup episode, Alex discusses the paper: 'Improving Organizers: Da Zheng, Vassilis N. Ioannidis, and Soji Adeshina Abstract: Graph

Graphdynamics Jl Efficient Scalable Neuronal - Detailed Analysis & Overview

Speaker: Spyros Chatzivasileiadis (DTU) Session: DTU Workshop on "Learning and Optimization for Decision-Making Under ... In this AI Research Roundup episode, Alex discusses the paper: 'Improving Organizers: Da Zheng, Vassilis N. Ioannidis, and Soji Adeshina Abstract: Graph What should Earth system modeling, and computational science more generally, look like in the era of deep learning and ... Luana Ruiz (University of Pennsylvania) Graph Limits, Nonparametric Models, and ... April 12, 2017 MIA Meeting: Matt Johnson Google Brain Composing graphical models ...

In this session of Machine Learning Tech Talks, Senior Research Scientist at DeepMind, Petar Veličković, will give an introductory ... Graph machine learning has become very popular in recent years in the machine learning and engineering communities.

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GraphDynamics.jl: Efficient, scalable neuronal dynamics | Protter | JuliaCon Global 2025
Spyros Chatzivasileiadis: Physics-Informed Graph Neural Networks for Power Systems
MD Decoupling: Stable Neural Network Training
EPFLx: Neuronal Dynamics: BIO465x About Video
NeuroDynamics.jl: Next generation models in neuroscience | ElGazzar | JuliaCon 2024
Tutorial: Scaling GNNs in Production: A Tale of Challenges and Opportunities
NeuralGCM
Machine Learning on Large-Scale Graphs
MIA: Matt Johnson, Composing graphical models with neural networks; Scott Linderman
Intro to graph neural networks (ML Tech Talks)
Deep learning with dynamic graph neural networks
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GraphDynamics.jl: Efficient, scalable neuronal dynamics | Protter | JuliaCon Global 2025

GraphDynamics.jl: Efficient, scalable neuronal dynamics | Protter | JuliaCon Global 2025

GraphDynamics

Spyros Chatzivasileiadis: Physics-Informed Graph Neural Networks for Power Systems

Spyros Chatzivasileiadis: Physics-Informed Graph Neural Networks for Power Systems

Speaker: Spyros Chatzivasileiadis (DTU) Session: DTU Workshop on "Learning and Optimization for Decision-Making Under ...

MD Decoupling: Stable Neural Network Training

MD Decoupling: Stable Neural Network Training

In this AI Research Roundup episode, Alex discusses the paper: 'Improving

EPFLx: Neuronal Dynamics: BIO465x About Video

EPFLx: Neuronal Dynamics: BIO465x About Video

The activity of

NeuroDynamics.jl: Next generation models in neuroscience | ElGazzar | JuliaCon 2024

NeuroDynamics.jl: Next generation models in neuroscience | ElGazzar | JuliaCon 2024

NeuroDynamics.

Tutorial: Scaling GNNs in Production: A Tale of Challenges and Opportunities

Tutorial: Scaling GNNs in Production: A Tale of Challenges and Opportunities

Organizers: Da Zheng, Vassilis N. Ioannidis, and Soji Adeshina Abstract: Graph

NeuralGCM

NeuralGCM

What should Earth system modeling, and computational science more generally, look like in the era of deep learning and ...

Machine Learning on Large-Scale Graphs

Machine Learning on Large-Scale Graphs

Luana Ruiz (University of Pennsylvania) https://simons.berkeley.edu/node/22611 Graph Limits, Nonparametric Models, and ...

MIA: Matt Johnson, Composing graphical models with neural networks; Scott Linderman

MIA: Matt Johnson, Composing graphical models with neural networks; Scott Linderman

April 12, 2017 MIA Meeting: https://youtu.be/5RA-TMwdpbw?t=3435 Matt Johnson Google Brain Composing graphical models ...

Intro to graph neural networks (ML Tech Talks)

Intro to graph neural networks (ML Tech Talks)

In this session of Machine Learning Tech Talks, Senior Research Scientist at DeepMind, Petar Veličković, will give an introductory ...

Deep learning with dynamic graph neural networks

Deep learning with dynamic graph neural networks

Graph machine learning has become very popular in recent years in the machine learning and engineering communities.