Key papers

• Local-Global Geometric Insights for Graph Neural Networks via Entropic Curvature (2026)
  Rachid Caich et al.
  5.49
• Singular value soft-thresholding via the polar decomposition (2026)
  Stephen Becker
  5.49
• Hilbert Operator for Progressive Encoding (HOPE): A Mathematical Framework for Deconstructing Learned Representations in Deep Networks (2026)
  Hossein Mobahi et al.
  5.01
• Local Synaptic Rules Can Implement a SIGReg Gradient Without Backpropagation (2026)
  Martin Andrews
  5.01
• Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks (2026)
  Masahiro Tanaka
  5.01
• Graph-Based Correlation Matrix Generation: A Convex Optimization Approach (2026)
  Ali Fakhar (UGA) et al.
  5.01
• Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights (2026)
  Naoya Chiba et al.
  4.39
• The Multiscale Single-Index Model: A Stylized Model for Hierarchical Feature Learning (2026)
  Joan Bruna
  4.39
• Manifold Constrained Tabular Deep Neural Networks (2026)
  Tian Li et al.
  4.39
• Learning in Curved Weight Space:Exponential-Linear Weight Reparameterization for Improved Optimization (2026)
  Ethan Smith
  4.39
• Instruction Set and Language for Hypergraphs (2026)
  Mario Pascual-Gonzalez et al.
  4.39
• The Differential Neural Tangent Kernel and Its Positivity (2026)
  Bangti Jin et al.
  4.39
• Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model (2026)
  Max Weinmann et al.
  4.39
• Graph Neural Networks for RFID-Based Spatial Geometry Inference in Spatial AI Systems (2026)
  Curtis Shull et al.
  4.39
• EquiFusion: Kinematics-Agnostic Human Motion Prediction via Equivariant Latent Diffusion (2026)
  Cecilia Curreli et al.
  4.39
• Implicit Neural Networks as Static Controllers: Certificates and Performance Separation (2026)
  Giuseppe C. Calafiore et al.
  4.39
• Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation (2026)
  Mauro Gonzalo Tarazona-Levano et al.
  4.39
• IG-GAN: A Generative Adversarial Network for Aerodynamic Data Generation Based on Intrinsic Geometry (2026)
  Ying Yan et al.
  4.39
• Tropical Circuits with Scalar Multiplication Gates (2026)
  Christoph Hertrich et al.
  4.39
• How to Tame Grokking: Representation Geometry as a Control Signal (2026)
  Maksim A Kazanskii
  4.39
• Gradient-Free Topology Adaptation for Power Flow Surrogates via In-Context Whitening (2026)
  Ayushi Jolotia et al.
  4.39
• DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales (2026)
  Kaihui Cheng et al.
  4.39
• SechKAN: Kolmogorov-Arnold Networks with Hyperbolic Secant Functions (2026)
  Hoang-Thang Ta
  4.39
• Spatio-Temporal Prediction of Unsteady Airfoil Aerodynamics Using Augmented Graph Neural Ordinary Differential Equations with Exogenous Controls (2026)
  Henrik Lange et al.
  4.39
• Cost Accounting for Reactive Computational Graphs: Exhaustive Sweeps, Sequential Mutation, and the Backward-Locality Gap (2026)
  Abdallah Khemais (ISITCOM et al.
  4.39
• ChemHyperMag: Physics-informed magnetic hypergraph learning improves molecular ADMET prediction (2026)
  Hexiao Ding et al.
  4.39
• Attractor Geometry Determines the Identifiability Limits of System Discovery (2026)
  Matteo Gallo et al.
  4.39
• Functional Equivalence and Geometric Diversity in Neural Network Approximations: An Empirical Characterization (2026)
  Anuragine S A et al.
  4.39
• Variational meta-learning inference for low dimensional neural system identification (2026)
  Matteo Rufolo et al.
  4.39
• Spectral Higher-Order Neural Networks Have Sharp Expressivity Bounds (2026)
  Gianluca Peri et al.
  4.39
• GEqTrain: A Configuration-Driven Framework for Retargeting Equivariant Graph Neural Networks Across 3D Scientific Tasks (2026)
  Daniele Angioletti et al.
  4.39
• Parallel Noising in Neural Markov Logic Networks (2026)
  Peter Jung et al.
  4.39
• Neural Kolmogorov Equations: Parallelizable Learning of Stochastic Dynamics under General Noise (2026)
  Arthur Bizzi et al.
  4.39
• Riemannian Deep Learning: Modules, Networks, and Geometries (2026)
  Chen Ziheng
  4.39
• Do Sheaf Neural Networks Use Holonomy? A Measure--Intervene--Control Study (2026)
  Ankit Grover et al.
  4.39
• An Isotropy-Preserving Spectral Cap for Muon: Theory and Three Case Studies (2026)
  Jiachun Li
  4.39
• A Graph Neural Network approach to zero-shot Digital Twins (2026)
  Alicia Tierz et al.
  4.39
• Towards Faithful Graph Explanations with Synergistic Edge Effects via Granular Balls (2026)
  Jiancu Chen et al.
  4.39
• Spectral Flow Certificates for Depth-Aware Long-Range Propagation in Graph Neural Networks (2026)
  Ranjan Veerabhadraswamy et al.
  4.39
• On the Depth Scalability of Logic Gate Networks (2026)
  Taegun An et al.
  4.39
• Neural Feature Governance: Extending Atom Prevalence (2026)
  Idris Karel Seunda Ekwe et al.
  4.39
• Data eccentricity, asymptotics of Gaussian RBF reproducing kernel Hilbert space, and kernel PCA (2026)
  Sergio A. Alvarez
  4.39
• LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks (2026)
  Shiyi Liu et al.
  4.39
• Multiplicity of Stable Attractors in Disordered Neural Models (2026)
  Raffaele Marino et al.
  4.39
• Beyond Negative-Ridge Endpoints: Mixed-Sign Spectral Regularization via Negative-Shifted Gradient Descent (2026)
  Peng Zhao
  4.39
• Operator Neural Jump ODEs: $L^2$-optimal prediction in function spaces (2026)
  Florian Krach et al.
  4.39
• Beyond ICA: Identifiability by Symmetry Breaking (2026)
  Pengzhou Wu
  4.39
• Domain-Prior-Regularized Graph Modeling for Anomaly Detection in Cyber-Physical Systems (2026)
  Youngseok Hwang et al.
  4.39
• Photonic reservoir computing with complex networks (2026)
  Sion Park et al.
  4.39
• Neural operator discovery from heterogeneous trajectories (2026)
  Zituo Chen et al.
  4.39
• Does Graph Compression Preserve Signal Propagation? (2026)
  Kawshik Banerjee et al.
  4.39
• Exploration of the generative capabilities of Boltzmann machines applied to social systems under the majority rule (2026)
  Mauricio A. Valle et al.
  4.39
• A Statistical Difference between Single-Layer Learning and Hierarchical Learning in Wide Neural Networks (2026)
  Sumio Watanabe
  4.39
• Learning to Optimize: Joint Routing and Flow Allocation on Sparse Non-Euclidean Networks (2026)
  Haomiao Sun et al.
  4.39
• Soft-Constrained Optimization of Latent Space in Variational Autoencoders (2026)
  Ye Shi
  4.39
• Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation (2026)
  Mihai Suteu et al.
  4.39
• Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities (2026)
  L\'eo Hein et al.
  4.39
• Perturbative-NeuSA: A Structured Spectral Framework for Time-Dependent PDEs (2026)
  Xianli Zhu et al.
  4.39
• Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects (2026)
  Phu Gia Hoang et al.
  4.39
• Incremental Sheaf Cohomology on Cellular Complexes: O(1)-in-n Lazy Edit Processing under Bounded Local Geometry (2026)
  Jason L. Volk
  4.33