Media Summary: Date: 10/15/25 Abstract: Graph Neural Networks (GNNs) have become a cornerstone for the application of LIVE COVERAGE: What the Hell did Trump just sign? Jim and Adam Kinzinger break it down. BE SURE TO FOLLOW OUR ... Joint work with Nathan Kutz: Discovering physical laws and ...

Ingo Scholtes On Deep Learning - Detailed Analysis & Overview

Date: 10/15/25 Abstract: Graph Neural Networks (GNNs) have become a cornerstone for the application of LIVE COVERAGE: What the Hell did Trump just sign? Jim and Adam Kinzinger break it down. BE SURE TO FOLLOW OUR ... Joint work with Nathan Kutz: Discovering physical laws and ... Fall 21 - Computational Social Science Seminar - lecture 8 Computational Social Science Seminar held by prof. Dirk Helbing. We often think of Large Language Models (LLMs) as all-knowing, but as the team reveals, they still struggle with the logic of a ... Künstliche Intelligenz (KI) und Data Science sind die Schlüsselmethoden unseres Jahrhunderts. Hier werden Daten nicht nur ...

Visualization of a dynamic network using NETVisualizer, a software developed at the Chair of Systems Design, ETH Zurich. pathpy is an OpenSource python package for the analysis of time series data on networks using higher- and multi-order network ... One of the main challenges for AI remains unsupervised

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Ingo Scholtes on "Deep Learning for Temporal Graphs"
LIVE: Does he even know what he signed? Adam Kinzinger and Lawrence Lessig
When is a network a network?
Deep Learning to Discover Coordinates for Dynamics: Autoencoders & Physics Informed Machine Learning
Ingo Scholtes: From networks to optimal higher-order models of complex systems
The "Final Boss" of Deep Learning
De Bruijn Goes Neural
Neu an der Uni - Prof. Ingo Scholtes - Machine Learning for Complex Networks
There Will Be a Scientific Theory of Deep Learning
Dynamic Network Visualization
Introducing pathpy 2.0
From Deep Learning of Disentangled Representations to Higher-level Cognition
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Ingo Scholtes on "Deep Learning for Temporal Graphs"

Ingo Scholtes on "Deep Learning for Temporal Graphs"

Date: 10/15/25 Abstract: Graph Neural Networks (GNNs) have become a cornerstone for the application of

LIVE: Does he even know what he signed? Adam Kinzinger and Lawrence Lessig

LIVE: Does he even know what he signed? Adam Kinzinger and Lawrence Lessig

LIVE COVERAGE: What the Hell did Trump just sign? Jim and Adam Kinzinger break it down. BE SURE TO FOLLOW OUR ...

When is a network a network?

When is a network a network?

Promotional video for paper:

Deep Learning to Discover Coordinates for Dynamics: Autoencoders & Physics Informed Machine Learning

Deep Learning to Discover Coordinates for Dynamics: Autoencoders & Physics Informed Machine Learning

Joint work with Nathan Kutz: https://www.youtube.com/channel/UCoUOaSVYkTV6W4uLvxvgiFA Discovering physical laws and ...

Ingo Scholtes: From networks to optimal higher-order models of complex systems

Ingo Scholtes: From networks to optimal higher-order models of complex systems

Fall 21 - Computational Social Science Seminar - lecture 8 Computational Social Science Seminar held by prof. Dirk Helbing.

The "Final Boss" of Deep Learning

The "Final Boss" of Deep Learning

We often think of Large Language Models (LLMs) as all-knowing, but as the team reveals, they still struggle with the logic of a ...

De Bruijn Goes Neural

De Bruijn Goes Neural

Temporal Graph

Neu an der Uni - Prof. Ingo Scholtes - Machine Learning for Complex Networks

Neu an der Uni - Prof. Ingo Scholtes - Machine Learning for Complex Networks

Künstliche Intelligenz (KI) und Data Science sind die Schlüsselmethoden unseres Jahrhunderts. Hier werden Daten nicht nur ...

There Will Be a Scientific Theory of Deep Learning

There Will Be a Scientific Theory of Deep Learning

Deep learning

Dynamic Network Visualization

Dynamic Network Visualization

Visualization of a dynamic network using NETVisualizer, a software developed at the Chair of Systems Design, ETH Zurich.

Introducing pathpy 2.0

Introducing pathpy 2.0

pathpy is an OpenSource python package for the analysis of time series data on networks using higher- and multi-order network ...

From Deep Learning of Disentangled Representations to Higher-level Cognition

From Deep Learning of Disentangled Representations to Higher-level Cognition

One of the main challenges for AI remains unsupervised

The Deep End of Deep Learning | Hugo Larochelle | TEDxBoston

The Deep End of Deep Learning | Hugo Larochelle | TEDxBoston

Artificial