Gradient estimation of probabilistic programs reduces soundly to probabilistic inference after programmable coupling and factorization, enabling new low-variance estimators that beat baselines.
2003.Monte Carlo Methods in Financial Engineering
3 Pith papers cite this work, alongside 3,938 external citations. Polarity classification is still indexing.
3
Pith papers citing it
3,938
external citations · OpenAlex
years
2026 3representative citing papers
The PROBE algorithm provably reduces the sample complexity of best-arm identification by using cheap proxy scores as control variates, achieving oracle-level savings even when the reward-proxy correlation is unknown.
A risk intelligence system for the Internet of Value combines prediction, verification, sentiment, agentic, and scenario engines, with limited Solana experiments claimed to support deployability.
citing papers explorer
-
GradInf: Gradient Estimation as Probabilistic Inference
Gradient estimation of probabilistic programs reduces soundly to probabilistic inference after programmable coupling and factorization, enabling new low-variance estimators that beat baselines.
-
Best-Arm Identification with Generative Proxy
The PROBE algorithm provably reduces the sample complexity of best-arm identification by using cheap proxy scores as control variates, achieving oracle-level savings even when the reward-proxy correlation is unknown.
-
Agentic, Context-Aware Risk Intelligence in the Internet of Value
A risk intelligence system for the Internet of Value combines prediction, verification, sentiment, agentic, and scenario engines, with limited Solana experiments claimed to support deployability.