Machine Learning

Papers
(The H4-Index of Machine Learning is 28. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-06-01 to 2025-06-01.)
ArticleCitations
The role of mutual information in variational classifiers198
Automated imbalanced classification via layered learning124
Learning to bid and rank together in recommendation systems119
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics110
Adapting performance metrics for ordinal classification to interval scale: length matters94
Fairness seen as global sensitivity analysis92
One-Stage Tree: end-to-end tree builder and pruner90
Multimodal deep learning for cetacean distribution modeling of fin whales (Balaenoptera physalus) in the western Mediterranean Sea82
Parameter identifiability of a deep feedforward ReLU neural network75
Compositional scene modeling with global object-centric representations71
Maximum causal entropy inverse constrained reinforcement learning63
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations59
Semantic-enhanced graph neural networks with global context representation54
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting54
Spike2CGR: an efficient method for spike sequence classification using chaos game representation53
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations49
Robust reputation independence in ranking systems for multiple sensitive attributes45
A review on instance ranking problems in statistical learning42
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers42
Invariant representation learning via decoupling style and spurious features41
Masked autoencoder for multiagent trajectories35
Chinese character recognition with radical-structured stroke trees34
Maintaining AUC and H-measure over time32
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization32
A flexible class of dependence-aware multi-label loss functions32
Towards accurate knowledge transfer via target-awareness representation disentanglement31
Learning any memory-less discrete semantics for dynamical systems represented by logic programs29
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization29
0.17576193809509