DOI,IST REx ID,Research Group,Title of publication
null,18118,ChLa,More flexible PAC-Bayesian meta-learning by learning learning algorithms
10.5311/JOSIS.2024.29.295,18856,ChLa,Predicting the geolocation of tweets using transformer models on customized data
null,18875,"GradSch,ChLa",Banded square root matrix factorization for differentially private model training
null,18891,"GradSch,MaMo,ChLa",Neural collapse versus low-rank bias: Is deep neural collapse really optimal?
10.48550/arXiv.2403.06833,19063,"GradSch,ChLa",Can LLMs separate instructions from data? And what do we even mean by that?
null,19408,ChLa,Continual learning: Applications and the road forward
null,17093,"DaAl,ChLa",Communication-efficient federated learning with data and client heterogeneity
null,17411,ChLa,PEFLL: Personalized federated learning by learning to learn
null,18120,ChLa,Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials
10.1109/CVPR52733.2024.02320,17426,"GradSch,ChLa","1-Lipschitz layers compared: Memory, speed, and certifiable robustness"
10.48550/arXiv.2412.04245,18874,"GradSch,ChLa",Intriguing properties of robust classification
10.1103/physrevb.108.125411,14320,"MaSe,ChLa,MiLe",Deep learning extraction of band structure parameters from density of states: A case study on trilayer graphene
10.1007/978-3-031-40773-4_6,14410,ChLa,"On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift"
10.2478/msr-2023-0023,14446,ChLa,Against the flow of time with multi-output models
null,12660,ChLa,Cross-client label propagation for transductive and semi-supervised federated learning
null,14921,"MaMo,ChLa",Deep neural collapse is provably optimal for the deep unconstrained features model
10.48550/ARXIV.2311.06103,15039,"GradSch,ChLa",1-Lipschitz neural networks are more expressive with N-activations
10.15479/at:ista:13074,13074,"GradSch,DaAl,ChLa",Efficiency and generalization of sparse neural networks
null,13053,"GradSch,DaAl,ChLa",CrAM: A Compression-Aware Minimizer
10.1109/cvpr52729.2023.02334,14771,"DaAl,ChLa",Bias in pruned vision models: In-depth analysis and countermeasures