Key papers

• Active Sensing for RIS-Aided Tracking and Power Control: A Hybrid Neuroevolution and Supervised Learning Approach (2026)
  George Stamatelis et al.
  4.39
• K-ABENA: K-Adaptive Backpropagation with Error-based N-exclusion Algorithm : (Compensated Loss-Based Sample Exclusion with Unbiased Gradient Estimation) (2026)
  Jean-Francois Bonbhel
  4.39
• Multi-layer MIMO Relay as Deep Physical Neural Networks: Power Amplifiers as Activation Functions (2026)
  Meng Hua et al.
  4.39
• Contraction-Gauge Preconditioning for Quantized Matrix Multiplication (2026)
  Piyush Sao et al.
  4.39
• On the Order-Conditional Optimality of Gaffke's Bound (2026)
  George Bissias et al.
  4.39
• Distributed Convolutional Rank Regression over Decentralized Networks (2026)
  Chunjing Li et al.
  4.39
• Learning Temporal Causal Structure via Smooth Differentiable Optimization (2026)
  Tong Zhao et al.
  4.33
• Data-dependent Evaluations for Budgeted Submodular Maximization (2026)
  Lejian Zhang et al.
  3.51
• Accelerated Mixing Time of Randomized Hamiltonian Monte Carlo (2026)
  Siddharth Mitra et al.
  3.51
• Structure-Specific Representational Priors Causally Control the Grokking Delay (2026)
  Gunner Levi Howe
  2.00
• Contextual Procurement Auctions with Bandit Learning (2026)
  Yiling Chen et al.
  2.00
• A Path Integral Model of Cognition (2026)
  Haruki Emori et al.
  2.00
• Stronger Memory-Query Tradeoffs for Convex Optimization: The Limitations of Subquadratic Memory (2026)
  Michael Menart et al.
  2.00
• Amortising Trajectory Optimisation for Residual MPC via Implicit Contact Differentiation (2026)
  Daniel Layeghi et al.
  2.00
• Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms (2026)
  Michael P\"urrer et al.
  2.00
• Generative Distributionally Robust Optimization (2026)
  Ziwei Zhang et al.
  2.00
• Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data (2026)
  Abhinav Chakraborty et al.
  2.00
• Guiding Posterior Exploration with Optimizer-Derived Geometry (2026)
  Moritz Schlager et al.
  2.00
• Rethinking Likelihood distributions: Student's t Likelihood Boosts Bayesian Neural Network Performance (2026)
  Pei-Hsuan Hsia et al.
  2.00
• Data-Dependent Regret and Polyak Corrections for Constrained Online Convex Optimization (2026)
  Wentao Zhang
  2.00
• Finding Optimal Cost-Bounded Plan Reductions: Refined Model (2026)
  Martha Del Toro et al.
  2.00
• Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise (2026)
  Bin Luo et al.
  2.00
• From Training to Deployment: Post-Hoc Causal Feature Identification via Sensitivity Ratios (2026)
  Athanasios Vlontzos et al.
  2.00
• Generalised Robust Bayes for Joint Inference of Model and Contamination (2026)
  Masahiro Fujisawa et al.
  2.00
• Optimization with Dynamic Constraint Learning (DCL) (2026)
  Ezgi Oztekin et al.
  2.00
• Variance-Reduced Conditional Gradient Methods under Markovian Sampling for Nonconvex Composite Optimization (2026)
  Zhaojun Peng
  2.00
• Causally Interpretable Meta-Mediation Analysis With Missing At Random Mediator and Outcome Data (2026)
  Marie-F\'elicia Beclin et al.
  2.00
• Optimal Ansatz-free Hamiltonian Learning In Situ (2026)
  Taiqi Zhou et al.
  1.94
• Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations (2026)
  Artur Miroszewski
  1.89
• GoQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization (2026)
  Maoyang Xiang et al.
  1.89
• Breaking the Curse of Repulsion: Remoteness-Aware Control of Negative Off-Policy Updates (2026)
  Yusen Huo et al.
  1.72
• Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes (2026)
  Yan Zhang et al.
  1.67
• The Ray Tracing Sampler: Bayesian Sampling of Neural Networks for Everyone (2025)
  Peter Behroozi
  1.50
• Towards real-time surrogate-free Bayesian inversion for neutron reflectometry (2025)
  Max D. Champneys et al.
  1.44
• Towards Efficient Inference under Nonmonotone Missingness with General Imputation (2025)
  Qi Xu et al.
  1.44
• A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes (2025)
  Meiliang Liu et al.
  1.33
• On the Convergence Analysis of Muon (2025)
  Wei Shen et al.
  1.22