A Scaling Hypothesis for the Euclidean Bipartite Matching Problem. - Sergio Caracciolo; Carlo Lucibello; Giorgio Parisi; Gabriele Sicuro (CoRR, 2014)

One-loop diagrams in the Random Euclidean Matching Problem. - Carlo Lucibello; Giorgio Parisi; Gabriele Sicuro (CoRR, 2016)

Recovery thresholds in the sparse planted matching problem. - Guilhem Semerjian; Gabriele Sicuro; Lenka Zdeborová (CoRR, 2020)

The planted k-factor problem. - Gabriele Sicuro; Lenka Zdeborová (CoRR, 2020)

Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions. - Bruno Loureiro; Gabriele Sicuro; Cédric Gerbelot; Alessandro Pacco; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2021)

Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions. - Bruno Loureiro; Gabriele Sicuro; Cédric Gerbelot; Alessandro Pacco; Florent Krzakala; Lenka Zdeborová (CoRR, 2021)

Aligning random graphs with a sub-tree similarity message-passing algorithm. - Giovanni Piccioli; Guilhem Semerjian; Gabriele Sicuro; Lenka Zdeborová (CoRR, 2021)

Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. - Bruno Loureiro; Cédric Gerbelot; Maria Refinetti; Gabriele Sicuro; Florent Krzakala (ICML, 2022)

Planted matching problems on random hypergraphs. - Urte Adomaityte; Anshul Toshniwal; Gabriele Sicuro; Lenka Zdeborová (CoRR, 2022)

Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach. - Urte Adomaityte; Gabriele Sicuro; Pierpaolo Vivo (NeurIPS, 2023)

Classification of Superstatistical Features in High Dimensions. - Urte Adomaityte; Gabriele Sicuro; Pierpaolo Vivo (CoRR, 2023)

High-dimensional robust regression under heavy-tailed data: Asymptotics and Universality. - Urte Adomaityte; Leonardo Defilippis; Bruno Loureiro; Gabriele Sicuro (CoRR, 2023)