Scalable Training of Continuous-Time Spiking Neural Networks with Differentiable
Continuous-time spiking neural networks (SNNs) provide an event-driven framework for temporal computation, computational neuroscience, and neuromorphic hardware. However, training deep continuous-time SNNs is severely constrained by the mem
https://arxiv.org/abs/2607.14672v1 ↗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 → stable
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Correct facts used on the next screening or memo.
People
Y
Yusuke Sakemi
1.0
low confidence
T
Tomoya Takeuchi
1.0
low confidence
T
Takeo Hosomi
1.0
low confidence
K
Kazuyuki Aihara
1.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
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Gordon Hirsch Wilson
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Strong Compute
· Active
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