MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model
Single-task fine-tuning of graph neural networks (GNNs) for power grid problems exhibits a systematic failure mode: models that achieve the lowest in-distribution error degrade the most under topology shift. We term this topology overfittin
https://arxiv.org/abs/2607.13763v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
None
How close the company’s idea is to your thesis statement
Sector
ai
Overlap with sectors you care about
Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↓ declining
▸ Add / edit details
Correct facts used on the next screening or memo.
People
C
Charilaos Papaioannou
1.0
low confidence
I
Ioannis Tsantilas
1.0
low confidence
D
Dimitris Giannakakos
1.0
low confidence
V
Vasilis Michalakopoulos
1.0
low confidence
S
Sotiris Pelekis
1.0
low confidence
V
Vangelis Marinakis
1.0
low confidence
A
Arsam Aryandoust
1.0
low confidence
A
Antonello Monti
1.0
low confidence
R
Ricardo J. Bessa
1.0
low confidence
P
Perdo P. Vergara
1.0
low confidence
J
Jochen Cremer
1.0
low confidence
E
Elissaios Sarmas
1.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
deepsilicon
· Inactive
Software and hardware to run neural networks faster and cheaper
founders not scraped yet
Gridware
· Active
Protecting the grid today, preparing the grid for tomorrow
founders not scraped yet