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Found 10 papers, 3 papers with code
Scaling Integer Arithmetic in Probabilistic Programs
Distributions on integers are ubiquitous in probabilistic modeling but remain challenging for many of today's probabilistic programming languages (PPLs).
flip-hoisting: Exploiting Repeated Parameters in Discrete Probabilistic Programs
Many of today's probabilistic programming languages (PPLs) have brittle inference performance: the performance of the underlying inference algorithm is very sensitive to the precise way in which the probabilistic program is written.
Counterexample-Guided Learning of Monotonic Neural Networks
Additionally, we propose a technique to use monotonicity as an inductive bias for deep learning.
Dice: Compiling Discrete Probabilistic Programs for Scalable Inference
This reduction separates the structure of the distribution from its parameters, enabling logical reasoning tools to exploit that structure for probabilistic inference.
Programming Languages
Overfitting in Synthesis: Theory and Practice (Extended Version)
A standard approach to mitigate overfitting in machine learning is to run multiple learners with varying expressiveness in parallel.
Generating and Sampling Orbits for Lifted Probabilistic Inference
A key goal in the design of probabilistic inference algorithms is identifying and exploiting properties of the distribution that make inference tractable.
Sound Abstraction and Decomposition of Probabilistic Programs
Experimentally, we also illustrate the practical benefits of our framework as a tool to decompose probabilistic program inference.
FlashProfile: A Framework for Synthesizing Data Profiles
However, manual inspection of data to identify the different formats is infeasible in standard big-data scenarios.
LoopInvGen: A Loop Invariant Generator based on Precondition Inference
We describe the LoopInvGen tool for generating loop invariants that can provably guarantee correctness of a program with respect to a given specification.
Probabilistic Program Abstractions
Abstraction is a fundamental tool for reasoning about complex systems.
