Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference
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Updated
Aug 24, 2026 - Python
Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference
Efficient and diverse virtual cell priors in JAX for end-to-end pretraining
Prior-fitted networks for time-series causal inference and longitudinal counterfactual outcome prediction.
Exploration of tabular data foundation models
Open-source toolkit + marketplace for prior-fitted foundation models (PFNs)
Can domain knowledge be encoded in a tabular foundation model's pretraining prior? TabICL prior design for credit-risk PD and LGD.
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