pith:XFV5UMRQ
ImmuVis: Hyperconvolutional Foundation Model for Imaging Mass Cytometry
ImmuVis generates convolutional kernels on the fly from marker embeddings so one model works with any combination of molecular markers in tissue images.
arxiv:2602.04585 v2 · 2026-02-04 · cs.CV
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Record completeness
Claims
ImmuVis introduces marker-adaptive hyperconvolutions that generate convolutional kernels from learned marker embeddings, enabling a single model to operate on arbitrary measured marker subsets without retraining.
That embeddings learned from the pretraining marker set can generate effective kernels for entirely new marker combinations never seen during training or fine-tuning.
ImmuVis uses hyperconvolutions generated from marker embeddings to create a foundation model that processes variable marker subsets in IMC images, pretrained on 17M patches and providing uncertainty estimates.
Receipt and verification
| First computed | 2026-05-17T23:39:16.357445Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b96bda3230e3b05059c04cc33c979d7b2ba996241ccb967284366eeb8206bc2a
Aliases
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XFV5UMRQ4OYFAWOAJTBTZF45PM \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: b96bda3230e3b05059c04cc33c979d7b2ba996241ccb967284366eeb8206bc2a
Canonical record JSON
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