Key papers

• Adaptive Reconstruction of Bosonic Quantum States (2026)
  Vasilisa Usova et al.
  5.54
• Monsoon Mayhem to Market Waves: Forecasting Fisheries Resilience in Sri Lanka (2026)
  Ruzaini Ahmed et al.
  5.54
• Unifying quantum measurement constructions via a relative-entropy minimum change principle (2026)
  Nana Liu et al.
  5.54
• Modeling Unknown Nonlocal PDE Systems via Flow Map Learning (2026)
  Zhongshu Xu et al.
  4.81
• Simulation-Based Plate-Reverb Parameter Estimation from a Single Impulse Response (2026)
  Minhui Lu et al.
  4.81
• Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics (2026)
  Fabio Pereira dos Santos et al.
  4.81
• Physics-informed neural networks for two-dimensional wall-reactive solute dispersion in canonical shear flows (2026)
  Nanda Poddar et al.
  4.81
• Sheaf-theoretic Signal Processing on Graphs: Spectral Theory, Filtering, and Sampling (2026)
  Gabriele D'Acunto et al.
  4.81
• Probabilistic Deep Learning for Drought Forecasting: Role of Internal Climate Variability (2026)
  Henri Funk et al.
  4.81
• Convex Neural Energy Elements: Monolithic Finite-Element Assembly of Geometry-Parameterized Neural Operators with Stability and Error Guarantees (2026)
  Hongyue Jiang et al.
  4.81
• Cardiovascular Digital Twins from Physics Based to Data Driven Approaches (2026)
  Emmanuel Lwele et al.
  4.81
• Neural network realization of binary refinement iterates via a two-chart atlas selector (2026)
  Tsogtgerel Gantumur
  4.81
• A Hyperfinite Framework for Score-Based Generative Modeling (2026)
  Sunder Ram Krishnan
  4.81
• Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models (2026)
  Edgar Jaber (CB et al.
  4.81
• Should the Boundary Term Be Learned in Reflected Diffusion? Conormal Trace and Reflection Masking (2026)
  Ziyue Wang et al.
  4.81
• A fully nonlinear structural vector autoregressive model identified via independent innovation analysis (2026)
  Savi Virolainen
  4.81
• Divide-and-Conquer: Towards Generalizable Amortized Bayesian Inference for the Drift Diffusion Model (2026)
  Yufei Wu et al.
  4.81
• Predicting Deep Neural Network Training Outcomes from Early Training Telemetry (2026)
  Ranjita Naik et al.
  4.81
• Information-Geometric Forward Policy Training in GFlowNets (2026)
  Yordan Raykov et al.
  4.81
• MINT: Tensor Decomposition on Stacked Recurrence Matrices for Time Series Data Mining (2026)
  Kaamil Kaka et al.
  4.81
• From Non-Convex Self-Concordant Regularization to Scalable Quasi-Newton Training of PINNs (2026)
  Chenhao Si et al.
  4.81
• Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling (2026)
  Parth Doshi et al.
  4.81
• Physics-informed reduced-order modelling with equivariant spectral submanifolds (2026)
  Georg Maierhofer
  4.81
• Tropical Algebraic Geometry for Neuronal Representations: An Arakelov-Green Measure Based Descriptor for Graph Learning (2026)
  Yuyang Zhang et al.
  4.81
• Potential Matching Optimal Transport: Continuous Normalizing Flows for Exact p-Wasserstein Dynamics (2026)
  Lishuo Zhang (School of Mathematical Sciences et al.
  4.81
• Fermat Active Laplace Learning for Semi-Supervised Hyperspectral Image Classification (2026)
  Vutichart Buranasiri et al.
  3.77
• AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning (2026)
  Shengyang Li et al.
  3.77
• Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling (2026)
  Nelson Aloysio Reis de Almeida Passos et al.
  3.77
• Geometry of Friston's active inference (2018)
  Martin Biehl
  —
• A Balance for Fairness: Fair Distribution Utilising Physics in Games of Characteristic Function Form (2021)
  Song-Ju Kim et al.
  —
• Quasi-Bayesian sequential deconvolution (2024)
  Stefano Favaro et al.
  —
• Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions (2024)
  Iskander Azangulov et al.
  —