DOI,IST REx ID,Research Group,Title of publication
10.15479/AT-ISTA-22258,22258,"GradSch,MaRo,MaMo",From sparse selection to risk prediction: Approximate message passing for proteomic survival models and large-scale genomics
10.1016/j.xgen.2026.101162,21488,"MaMo,MaRo",Joint modeling of whole-genome sequencing data for human height via approximate message passing
10.1137/24m1702854,22228,MaMo,Precise asymptotics for spectral methods in mixed generalized linear models
10.1103/PhysRevResearch.7.013081,18986,MaMo,Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise
10.1073/pnas.2423072122,19627,MaMo,Privacy for free in the overparameterized regime
10.4171/MSL/52,20734,MaMo,Spectral estimators for structured generalized linear models via approximate message passing
10.1109/TIT.2024.3367767,15172,MaMo,Concentration without independence via information measures
null,18890,"GradSch,MaMo",Average gradient outer product as a mechanism for deep neural collapse
null,18891,"GradSch,MaMo,ChLa",Neural collapse versus low-rank bias: Is deep neural collapse really optimal?
null,18897,"JaMa,MaMo",Improved convergence of score-based diffusion models via prediction-correction
null,18972,MaMo,How spurious features are memorized: Precise analysis for random and NTK features
null,18973,MaMo,Towards understanding the word sensitivity of attention layers: A study via random features
10.48550/arXiv.2305.14164,17350,"JaMa,MaMo",Improved convergence of score-based diffusion models via prediction-correction
10.1109/ICASSP48485.2024.10447198,17147,"MaMo,MaRo",Inference of genetic effects via approximate message passing
10.15479/at:ista:17465,17465,"GradSch,DaAl,MaMo",High-dimensional limits in artificial neural networks
null,17469,"DaAl,MaMo",Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth
null,12859,"GradSch,MaMo",Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels
10.1073/pnas.2302028120,13315,MaMo,Fundamental limits in structured principal component analysis and how to reach them
10.1109/isit54713.2023.10206899,14922,MaMo,Concentration without independence via information measures
null,14924,MaMo,"Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence"