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[OOPSLA] Approximate Computation with Outlier Detection in Topaz
[OOPSLA'25] Structural Information Flow: A Fresh Look at Types for Non-Interference
Effects as Capabilities: Effect Handlers and Lightweight Effect Polymorphism (OOPSLA'20)
[PLDI'26] GradInf: Gradient Estimation as Probabilistic Inference
[PLDI'26] [SIGPLAN OOPSLA’25] Active Learning for Neurosymbolic Program Synthesis
[POPL'26] Local Contextual Type Inference
[ProLaLa24] The Future of ProLaLa
[OOPSLA] Synthesis of Layout Engines from Relational Constraints
Fritz Obermeyer - Probabilistic Programming and Readable Models | PyData Yerevan 2022
Uncovering the Unknown: Principles of Type Inference
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Last Updated: August 14, 2026
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![[OOPSLA] Synthesis of Layout Engines from Relational Constraints](https://i.ytimg.com/vi/ehFHpo2YiPo/mqdefault.jpg)
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