Downlink Power Control in Dense 5G Radio Access Networks Through Deep Reinforcement Learning. - Sara Saeidian; Soma Tayamon; Euhanna Ghadimi (ICC, 2020)

Optimal Maximal Leakage-Distortion Tradeoff. - Sara Saeidian; Giulia Cervia; Tobias J. Oechtering; Mikael Skoglund (ITW, 2021)

Quantifying Membership Privacy via Information Leakage. - Sara Saeidian; Giulia Cervia; Tobias J. Oechtering; Mikael Skoglund (IEEE Trans. Inf. Forensics Secur., 2021)

Pointwise Maximal Leakage on General Alphabets. - Sara Saeidian; Giulia Cervia; Tobias J. Oechtering; Mikael Skoglund (ISIT, 2023)

Inferential Privacy: From Impossibility to Database Privacy. - Sara Saeidian; Giulia Cervia; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2023)

Pointwise Maximal Leakage. - Sara Saeidian; Giulia Cervia; Tobias J. Oechtering; Mikael Skoglund (IEEE Trans. Inf. Theory, 2023)

Evaluating Differential Privacy on Correlated Datasets Using Pointwise Maximal Leakage. - Sara Saeidian; Tobias J. Oechtering; Mikael Skoglund (APF, 2024)

Quantifying Privacy via Information Density. - Leonhard Grosse; Sara Saeidian; Parastoo Sadeghi; Tobias J. Oechtering; Mikael Skoglund (ISIT, 2024)

Information Density Bounds for Privacy. - Sara Saeidian; Leonhard Grosse; Parastoo Sadeghi; Mikael Skoglund; Tobias J. Oechtering (CoRR, 2024)

Extremal Mechanisms for Pointwise Maximal Leakage. - Leonhard Grosse; Sara Saeidian; Tobias J. Oechtering (IEEE Trans. Inf. Forensics Secur., 2024)

Pointwise Maximal Leakage: Robust, Flexible and Explainable Privacy ; Punktvist Maximalt Läckage: Robust, Flexibel och Förklarbar Dataintegritet. - Sara Saeidian (2024)

Rethinking Disclosure Prevention with Pointwise Maximal Leakage. - Sara Saeidian; Giulia Cervia; Tobias J. Oechtering; Mikael Skoglund (J. Priv. Confidentiality, 2025)

Strong Data Processing Properties of Rényi-divergences via Pinsker-type Inequalities. - Leonhard Grosse; Sara Saeidian; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2025)