• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 157 matches

• 2025
• 
  Carmen Plaza-Seco, Kenneth E. Barner, Roberto Holgado-Cuadrado, Francisco Manuel Melgarejo-Meseguer, José Luis Rojo-Álvarez, Manuel Blanco-Velasco:
  Detection of intra-beat waves on ambulatory ECG using manifolds: An explainable deep learning approach. Biomed. Signal Process. Control. 105: 107523 (2025)
• 
  Hrushikesh N. Mhaskar, Ryan O'Dowd:
  Learning on manifolds without manifold learning. Neural Networks 181: 106759 (2025)
• 
  Shangding Gu, Puze Liu, Alap Kshirsagar, Guang Chen, Jan Peters, Alois Knoll:
  ROSCOM: Robust Safe Reinforcement Learning on Stochastic Constraint Manifolds. IEEE Trans Autom. Sci. Eng. 22: 5841-5851 (2025)
• 
  Defu Yang, Hui Shen, Minghan Chen, Shuai Wang, Jiazhou Chen, Hongmin Cai, Xueli Chen, Guorong Wu, Wentao Zhu:
  A Novel Spatio-Temporal Hub Identification in Brain Networks by Learning Dynamic Graph Embedding on Grassmannian Manifolds. IEEE Trans. Medical Imaging 44(3): 1454-1467 (2025)
• 
  Daning Huang, Hanyang He, John Harlim, Yan Li:
  Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels. ICLR 2025
• 
  Giuseppe Bruno De Luca:
  Machine Learning Gravity Compactifications on Negatively Curved Manifolds. CoRR abs/2501.00093 (2025)
• 
  Dimitris G. Giovanis, Ellis R. Crabtree, Roger G. Ghanem, Ioannis G. Kevrekidis:
  Generative Learning of Densities on Manifolds. CoRR abs/2503.03963 (2025)
• 
  Aoran Chen, Yang Feng:
  GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds. CoRR abs/2505.02972 (2025)
• 
  Zhaiming Shen, Alex Havrilla, Rongjie Lai, Alexander Cloninger, Wenjing Liao:
  Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights. CoRR abs/2505.03205 (2025)
• 2024
• 
  Tilman Daab, Noémie Jaquier, Christian R. G. Dreher, André Meixner, Franziska Krebs, Tamim Asfour:
  Incremental Learning of Full-Pose Via-Point Movement Primitives on Riemannian Manifolds. ICRA 2024: 2317-2323
• 
  Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Ullrich Köthe:
  Learning Distributions on Manifolds with Free-Form Flows. NeurIPS 2024
• 
  Hrushikesh N. Mhaskar, Ryan O'Dowd:
  Learning on manifolds without manifold learning. CoRR abs/2402.12687 (2024)
• 
  Zhenwei Huang, Wen Huang, Pratik Jawanpuria, Bamdev Mishra:
  Federated Learning on Riemannian Manifolds with Differential Privacy. CoRR abs/2404.10029 (2024)
• 
  Vladimir Jacimovic:
  Kuramoto Oscillators and Swarms on Manifolds for Geometry Informed Machine Learning. CoRR abs/2405.09453 (2024)
• 
  Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy:
  The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. CoRR abs/2407.08086 (2024)
• 
  Osbert Bastani:
  Parameter Estimation for Generalized Low-Rank Matrix Sensing by Learning on Riemannian Manifolds. CoRR abs/2407.10238 (2024)
• 
  Christian Soize, Roger G. Ghanem:
  Transient anisotropic kernel for probabilistic learning on manifolds. CoRR abs/2407.21435 (2024)
• 
  Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Chen Liu, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy:
  Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. CoRR abs/2410.12779 (2024)
• 2023
• 
  Niccolò Guiducci, Claudio Tortorici, Claudio Ferrari, Stefano Berretti:
  Learning graph-based features for relief patterns classification on mesh manifolds. Comput. Graph. 115: 69-80 (2023)
• 
  John Harlim, Shixiao Willing Jiang, John Wilson Peoples:
  Radial Basis Approximation of Tensor Fields on Manifolds: From Operator Estimation to Manifold Learning. J. Mach. Learn. Res. 24: 345:1-345:85 (2023)
• 
  Zhi Gao, Yuwei Wu, Xiaomeng Fan, Mehrtash Harandi, Yunde Jia:
  Learning to Optimize on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5935-5952 (2023)
• 
  Byung Hyung Kim, Jin Woo Choi, Honggu Lee, Sungho Jo:
  A discriminative SPD feature learning approach on Riemannian manifolds for EEG classification. Pattern Recognit. 143: 109751 (2023)
• 
  Matteo Saveriano, Fares J. Abu-Dakka, Ville Kyrki:
  Learning stable robotic skills on Riemannian manifolds. Robotics Auton. Syst. 169: 104510 (2023)
• 
  Marissa Catherine Connor, Kion Fallah, Christopher John Rozell:
  Learning Identity-Preserving Transformations on Data Manifolds. Trans. Mach. Learn. Res. 2023 (2023)
• 
  Juan Cerviño, Luiz F. O. Chamon, Benjamin David Haeffele, René Vidal, Alejandro Ribeiro:
  Learning Globally Smooth Functions on Manifolds. ICML 2023: 3815-3854
• 
  Karthik Elamvazhuthi, Xuechen Zhang, Samet Oymak, Fabio Pasqualetti:
  Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs. L4DC 2023: 1-11
• 
  Adnan Ahmad, Wei Luo, Antonio Robles-Kelly:
  Federated Learning Under Statistical Heterogeneity on Riemannian Manifolds. PAKDD (1) 2023: 380-392
• 
  Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren:
  SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds. WWW 2023: 360-371
• 
  Yihao Fang, Ilsang Ohn, Vijay Gupta, Lizhen Lin:
  Intrinsic and extrinsic deep learning on manifolds. CoRR abs/2302.08606 (2023)
• 
  Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren:
  SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds. CoRR abs/2305.03883 (2023)

skipping 127 more matches