Scenic: a language for scenario specification and scene generation
We propose a new probabilistic programming language for the design and analysis of
perception systems, especially those based on machine learning. Specifically, we consider …
perception systems, especially those based on machine learning. Specifically, we consider …
Unifying logic and probability
S Russell - Communications of the ACM, 2015 - dl.acm.org
Unifying logic and probability Page 1 88 COMMUNICATIONS OF THE ACM | JULY 2015 | VOL.
58 | NO. 7 review articles DOI:10.1145/2699411 Open-universe probability models show merit …
58 | NO. 7 review articles DOI:10.1145/2699411 Open-universe probability models show merit …
Probabilistic programming
Probabilistic programs are usual functional or imperative programs with two added
constructs:(1) the ability to draw values at random from distributions, and (2) the ability to …
constructs:(1) the ability to draw values at random from distributions, and (2) the ability to …
Scenic: A language for scenario specification and data generation
We propose a new probabilistic programming language for the design and analysis of cyber-
physical systems, especially those based on machine learning. We consider several …
physical systems, especially those based on machine learning. We consider several …
PSI: Exact Symbolic Inference for Probabilistic Programs
Probabilistic inference is a key mechanism for reasoning about probabilistic programs.
Since exact inference is theoretically expensive, most probabilistic inference systems today …
Since exact inference is theoretically expensive, most probabilistic inference systems today …
Probabilistic smart contracts: Secure randomness on the blockchain
K Chatterjee, AK Goharshady… - … on blockchain and …, 2019 - ieeexplore.ieee.org
In today's programmable blockchains, smart contracts are limited to being deterministic and
non-probabilistic. This lack of randomness is a consequential limitation, given that a wide …
non-probabilistic. This lack of randomness is a consequential limitation, given that a wide …
Fairsquare: probabilistic verification of program fairness
A Albarghouthi, L D'Antoni, S Drews… - Proceedings of the ACM on …, 2017 - dl.acm.org
With the range and sensitivity of algorithmic decisions expanding at a break-neck speed, it is
imperative that we aggressively investigate fairness and bias in decision-making programs …
imperative that we aggressively investigate fairness and bias in decision-making programs …
Scaling exact inference for discrete probabilistic programs
Probabilistic programming languages (PPLs) are an expressive means of representing and
reasoning about probabilistic models. The computational challenge of probabilistic …
reasoning about probabilistic models. The computational challenge of probabilistic …
Detecting flaky tests in probabilistic and machine learning applications
Probabilistic programming systems and machine learning frameworks like Pyro, PyMC3,
TensorFlow, and PyTorch provide scalable and efficient primitives for inference and training …
TensorFlow, and PyTorch provide scalable and efficient primitives for inference and training …
Probabilistic verification of fairness properties via concentration
As machine learning systems are increasingly used to make real world legal and financial
decisions, it is of paramount importance that we develop algorithms to verify that these …
decisions, it is of paramount importance that we develop algorithms to verify that these …