18 citations · 25 across the 7 of their papers we have counts for
7 papers
Bluebell: An Alliance of Relational Lifting and Independence For Probabilistic Reasoning
Jialu Bao, Emanuele D'Osualdo, Azadeh Farzan
We present Bluebell, a program logic for reasoning about probabilistic programs where unary and relational styles of reasoning come together to create new reasoning tools. Unary-st…
A Categorical Approach to DIBI Models
Tao Gu, Jialu Bao, Justin Hsu +2
The logic of Dependence and Independence Bunched Implications (DIBI) is a logic to reason about conditional independence (CI); for instance, DIBI formulas can characterise CI in pr…
A Separation Logic for Negative Dependence
Jialu Bao, Marco Gaboardi, Justin Hsu +1
Formal reasoning about hashing-based probabilistic data structures often requires reasoning about random variables where when one variable gets larger (such as the number of elemen…
Structure Amplification on Multi-layer Stochastic Block Models
Xiaodong Xin, Kun He, Jialu Bao +2
Much of the complexity of social, biological, and engineered systems arises from a network of complex interactions connecting many basic components. Network analysis tools have bee…
Data-Driven Invariant Learning for Probabilistic Programs
Jialu Bao, Nitesh Trivedi, Drashti Pathak +2
Morgan and McIver's weakest pre-expectation framework is one of the most well-established methods for deductive verification of probabilistic programs. Roughly, the idea is to gene…
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers
Lunjia Hu, Omer Reingold
We study the problem of robustly estimating the mean of a -dimensional distribution given examples, where most coordinates of every example may be missing and $\varepsilon N…
Hidden Community Detection on Two-layer Stochastic Models: a Theoretical Perspective
Jialu Bao, Kun He, Xiaodong Xin +2
Hidden community is a new graph-theoretical concept recently proposed [4], in which the authors also propose a meta-approach called HICODE (Hidden Community Detection) for detectin…