Papers

• EVOTS: Evolutionary Transformer Search for Time Series Forecasting (2026)
  AbdElRahman ElSaid et al.
  5.01
• Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings (2026)
  Riley Acker et al.
  5.01
• Free energy landscape of Dense Associative Memory (2026)
  Sumedha et al.
  4.39
• MMAO-Cls: Metabolic Multi-Agent Optimization for Joint Feature Selection and Classifier Tuning (2026)
  Jinliang Xu et al.
  3.51
• Evolutionary Wave Function Collapse (2026)
  Dipika Rajesh et al.
  3.51
• Predicting Early Stages Of Alzheimer's Disease And Identifying Key Biomarkers Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies (2026)
  Debopriya Ghosh
  3.51
• Local Synaptic Rules Can Implement a SIGReg Gradient Without Backpropagation (2026)
  Martin Andrews
  2.00
• Shallower ReLU Network Representations via Exact Linear Algebra (2026)
  Kilian Rue{\ss} et al.
  2.00
• Combining Trained Models in Reinforcement Learning (2026)
  Ujjwal Patil et al.
  1.89
• Federated Few-Shot Learning on Neuromorphic Hardware: An Empirical Study Across Physical Edge Nodes (2026)
  Steven Motta and Gioele Nanni
  1.78
• Gradient Projection onto Historical Descent Directions for Communication-Efficient Federated Learning (2025)
  Arnaud Descours (UCBL) et al.
  1.56
• FedL2T: Personalized Federated Learning with Two-Teacher Distillation for Seizure Prediction (2025)
  Jionghao Lou et al.
  1.50
• ATM: Improving Model Merging by Alternating Tuning and Merging (2024)
  Luca Zhou et al.
  0.94
• Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI (2022)
  Joshua Durso-Finley et al.
  —
• PRANC: Pseudo RAndom Networks for Compacting deep models (2022)
  Parsa Nooralinejad et al.
  —
• A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry (2023)
  Jianfeng Wu et al.
  —
• Tangent Model Composition for Ensembling and Continual Fine-tuning (2023)
  Tian Yu Liu and Stefano Soatto
  —
• Enhancing Neural Training via a Correlated Dynamics Model (2023)
  Jonathan Brokman et al.
  —
• Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks (2024)
  Xin-Chun Li et al.
  —
• A High Energy-Efficiency Multi-core Neuromorphic Architecture for Deep SNN Training (2024)
  Mingjing Li et al.
  —