physics.comp-ph

Papers

• GenSBI: Generative Methods for Simulation-Based Inference in JAX (2026)
  Aurelio Amerio
  3.91
• Physics-informed neural networks for one-dimensional sound field predictions with parameterized sources and impedance boundaries (2023)
  Nikolas Borrel-Jensen and Allan P. Engsig-Karup and Cheol-Ho Jeong
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• j-Wave: An open-source differentiable wave simulator (2022)
  Antonio Stanziola et al.
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• Sinc Kolmogorov-Arnold network and its application for solving PDEs with singularities (2026)
  Tianchi Yu et al.
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• Timing and Dynamics of the Rosanna Shuffle (2024)
  Esa R\"as\"anen et al.
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• An Efficient Learning Method to Connect Observables (2026)
  Hang Yu et al.
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• Fast Differentiable Modal Simulation of Non-linear Strings, Membranes, and Plates (2025)
  Rodrigo Diaz et al.
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• Learning Nonlinear Dynamics in Physical Modelling Synthesis using Neural Ordinary Differential Equations (2025)
  Victor Zheleznov et al.
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• Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames (2026)
  Haiyang Yu et al.
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• MiAD: Mirage Atom Diffusion for De Novo Crystal Generation (2026)
  Andrey Okhotin et al.
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• Consistent Projection of Langevin Dynamics: Preserving Thermodynamics and Kinetics in Coarse-Grained Models (2026)
  Vahid Nateghi et al.
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• Differential syntactic and semantic encoding in LLMs (2026)
  Santiago Acevedo et al.
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• FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates (2026)
  Zishuo Lan et al.
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• Generative Neural Operators through Diffusion Last Layer (2026)
  Sungwon Park et al.
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• Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State (2026)
  Nicholas Gao et al.
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• Miller-Index-Based Latent Crystallographic Fracture Plane Reasoning and generation with Vision-Language Models (2026)
  Qinwu Xu et al.
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• The physics of AI weather models (2026)
  George Craig et al.
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• Harnessing AtomisticSkills for Agentic Atomistic Research (2026)
  Bowen Deng et al.
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• Implicit Binarization via Complex Phase Dynamics in Combinatorial Optimization (2026)
  Khen Cohen et al.
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• Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs (2026)
  Jinjin He et al.
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• A comparative study of accuracy and rollout stability of temporal surrogate models (2026)
  Rajarshi Biswas
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• Learning, locomotion, and navigation of soft synthetic snakes in three-dimensional, heterogeneous environments (2026)
  Xiaotian Zhang et al.
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• PDEInvBench: A Comprehensive Dataset and Design Space Exploration of Neural Networks for PDE Inverse Problems (2026)
  Divyam Goel et al.
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• Machine Learning Multiscale Interactions (2026)
  \`Alex Sol\'e et al.
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• Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers (2026)
  Shyam Sankaran et al.
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• Neural Autoregressive Control Variates for the Quantum Monte Carlo Sign Problem (2026)
  Bei Qiao et al.
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• High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention (2026)
  Deepak Akhare et al.
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• Adapting Automotive Aerodynamics Surrogates to New Vehicle Families via Transfer Learning (2026)
  Seunghwan Keum et al.
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• Hybrid Neural World Models (2026)
  Pranav Lakshmanan et al.
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• Thermodynamic properties of chemically disordered compounds via AI-driven estimation of partition function with the PULSE method (2026)
  Baptiste Bernard et al.
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• History-aware adaptive reduced-order models via incremental singular value decomposition (2026)
  Amirpasha Hedayat et al.
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• The Hamilton-Jacobi Theory of Deep Learning (2026)
  Jose Marie Antonio Mi\~noza et al.
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• Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization (2026)
  Yuxin Wang et al.
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