Computational Mechanics papers
Pofolia’s corpus holds 81 papers from Computational Mechanics (2012–2026), each with a short summary. Below, the 20 most-cited, then the most recently added.
At a glance
- Most cited: PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017, 9,803 citations).
- The 20 papers listed have 80,475 citations between them.
- 7 of the 8 with a known journal quartile appeared in a Q1 journal.
- 5 have a free full text (open access).
- Most frequent journals: arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics.
- Published between 2012 and 2021.
Most cited
Ranked by citation count. Because citations accumulate over time, this list naturally leans towards work published a few years ago; for where the field is now, see “recently added”. How to read the signals
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
2017 · 9,803 citations
PointNet is a novel neural network architecture designed to directly process irregular 3D point cloud data, bypassing the need for computationally expensive transformations into voxel grids or images.
UMAP: Uniform Manifold Approximation and Projection
The Journal of Open Source Software · 2018 · FWCI 391.51 · 9,692 citations · Open access
UMAP is a new dimension reduction technique offering both visualization and general non-linear reduction capabilities, built on a rigorous mathematical foundation but with a user-friendly API.
Decoupled Weight Decay Regularization
arXiv (Cornell University) · 2017 · 9,135 citations · Open access
A new method decouples weight decay from gradient updates in adaptive optimization algorithms like Adam, improving generalization performance.
Dynamic Graph CNN for Learning on Point Clouds
ACM Transactions on Graphics · 2019 · Q1 · SJR 5.00 · FWCI 461.40 · 6,795 citations · Open access
A new neural network module, EdgeConv, is introduced for processing 3D point cloud data, dynamically computing graph structures in each layer to capture local neighborhood information and learn global shape properties.
Robust Recovery of Subspace Structures by Low-Rank Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2012 · Q1 · SJR 4.00 · FWCI 144.98 · 3,666 citations
A new method called Low-Rank Representation (LRR) can accurately identify underlying subspace structures in data, even when the data contains outliers or sparse errors.
SMPL
ACM Transactions on Graphics · 2015 · Q1 · SJR 5.00 · FWCI 57.08 · 3,661 citations
A new Skinned Multi-Person Linear (SMPL) model accurately represents diverse human body shapes and poses, outperforming previous methods.
Geometric Deep Learning: Going beyond Euclidean data
IEEE Signal Processing Magazine · 2017 · Q1 · SJR 2.00 · FWCI 237.05 · 3,646 citations
Geometric deep learning (GDL) extends deep neural networks to non-Euclidean data like graphs and manifolds, enabling analysis of complex, structured information.
New development in freefem++
Journal of Numerical Mathematics · 2012 · Q1 · SJR 1.00 · FWCI 92.57 · 3,300 citations
This abstract provides no specific findings or results regarding developments in freefem++.
Sparse Subspace Clustering: Algorithm, Theory, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2013 · Q1 · SJR 4.00 · FWCI 173.72 · 3,155 citations
A new algorithm, Sparse Subspace Clustering (SSC), is proposed to group high-dimensional data points that naturally reside in multiple lower-dimensional structures.
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
arXiv (Cornell University) · 2012 · 2,980 citations · Open access
A new approximate inference algorithm enables efficient computation for fully connected Conditional Random Fields (CRFs) with Gaussian edge potentials, allowing dense pixel-level connections in image segmentation.
PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud
2019 · 2,977 citations
PointRCNN introduces a novel two-stage framework that directly generates 3D object proposals from raw point clouds, bypassing the need for RGB images or intermediate representations like bird's-eye view or voxels.
Introduction to the Finite Element Method
Cambridge University Press eBooks · 2021 · FWCI 202.40 · 2,945 citations
This innovative teaching package integrates theoretical learning with practical application of the Finite Element Method (FEM) using computational software like MATLAB®, PTC Creo Parametric, ANSYS APDL, ANSYS Workbench, and SolidWorks.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
arXiv (Cornell University) · 2016 · 2,880 citations · Open access
PointNet is a novel neural network architecture designed to directly process irregular 3D point cloud data, overcoming the limitations of converting it to voxel grids or images.
PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB
Journal of Open Research Software · 2014 · Q3 · FWCI 76.81 · 2,420 citations
A new open-source MATLAB tool, PIVlab, has been developed to address challenges in Digital Particle Image Velocimetry (DPIV) for accurate flow field mapping.
Thermal Radiation Heat Transfer
2020 · FWCI 126.68 · 2,377 citations
The seventh edition of this textbook updates fundamental principles and analytical/numerical techniques for thermal radiation heat transfer, incorporating expanded sections on surface properties, electromagnetic theory, scattering, absorption, near-field transfer, and connections to thermodynamics.
Deep Learning for 3D Point Clouds: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2020 · Q1 · SJR 4.00 · FWCI 180.65 · 2,272 citations
This paper surveys recent deep learning methods for 3D point cloud processing, covering classification, object detection/tracking, and segmentation.
Weighted Nuclear Norm Minimization with Application to Image Denoising
2014 · 2,271 citations
This paper introduces Weighted Nuclear Norm Minimization (WNNM), a novel approach that assigns different weights to singular values, enhancing flexibility over standard nuclear norm minimization. Applied to image denoising, WNNW significantly outperforms existing methods like BM3D.
Point Transformer
2021 IEEE/CVF International Conference on Computer Vision (ICCV) · 2021 · 2,219 citations
A novel 'Point Transformer' architecture leverages self-attention mechanisms for 3D point cloud processing, achieving state-of-the-art results in tasks like semantic scene segmentation.
Proximal Algorithms
Foundations and Trends® in Optimization · 2014 · FWCI 217.11 · 2,166 citations
Proximal algorithms are presented as a powerful, general-purpose tool analogous to Newton's method, specifically designed for complex optimization problems like nonsmooth, constrained, large-scale, or distributed versions.
Multiphase Flow And Fluidization: Continuum And Kinetic Theory Descriptions
2012 · 2,115 citations
This book bridges theoretical multiphase flow with practical, predictive solutions for industrial fluidization problems, advancing the emerging science of multiphase flow.
Recently added
Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions
Mathematical Models and Methods in Applied Sciences · 2026 · Q1 · SJR 1.00 · 2 citations · Open access
Deep neural networks (DNNs) with ReLU or ReLU 2 activations can precisely represent Lagrange finite element functions of any order on arbitrary simplicial meshes in any dimension.
Robust, randomized preconditioning for kernel ridge regression
Advances in Computational Mathematics · 2026 · Q1 · 1 citations
Two new randomized preconditioners (RPCholesky and KRILL) significantly speed up kernel ridge regression for large datasets (N=10^4 to 10^7) compared to existing methods.
Advanced Small Perturbation Potential Flow Theory for Unsteady Aerodynamic and Aeroelastic Analyses
Journal of Aircraft · 2026 · Q2 · 8 citations · Open access
A new Advanced Small Perturbation (ASP) potential flow theory, incorporating entropy, vorticity, and viscous effects, offers greater mathematical appropriateness and computational accuracy than classical Transonic Small Perturbation (TSP) theories for unsteady aerodynamic and aeroelastic analyses.
Viscous Implicit Overset Method for High-Speed Compressible Flows
AIAA Journal · 2026 · Q1 · FWCI 4.34 · 1 citations
A novel viscous implicit overset method simplifies grid generation for complex geometries in high-speed compressible flow simulations, enabling larger time steps and reduced simulation times.
Pressure-Robust Staggered DG Methods for the Navier–Stokes Equations on General Meshes
Journal of Scientific Computing · 2026 · Q1 · SJR 1.00 · 2 citations · Open access
New staggered discontinuous Galerkin (DG) methods for Navier-Stokes equations ensure velocity accuracy is independent of pressure and Reynolds number for small rotational forces.
Investigating Non-Newtonian Fluid Behavior in Hydrocyclones Via Computational Fluid Dynamics
International Journal of Innovative Science and Research Technology (IJISRT) · 2024 · FWCI 314.54 · 958 citations
A CFD study of viscoelastic food in hydrocyclones reveals how viscosity fluctuations impact particle separation efficiency, providing insights for optimizing food processing technology.
ShapeNet: An Information-Rich 3D Model Repository
2023 · FWCI 14.38 · 1,999 citations
ShapeNet is a new large-scale repository of 3D CAD models, organized by semantic categories and annotated with detailed information like alignments, parts, and symmetry planes.
Point Transformer
2021 IEEE/CVF International Conference on Computer Vision (ICCV) · 2021 · 2,219 citations
A novel 'Point Transformer' architecture leverages self-attention mechanisms for 3D point cloud processing, achieving state-of-the-art results in tasks like semantic scene segmentation.
Journals in this field
The journals that publish most of this field’s papers. Quartile (Q1–Q4), SJR and h-index are from SCImago Journal Rank; “in this field” is how many of the journal’s pooled papers belong here. What is a Q1 journal? · What is the h-index?
| Journal | Quartile | SJR | h-index | In this field | Summaries |
|---|---|---|---|---|---|
| IEEE Transactions on Pattern Analysis and Machine Intelligence | Q1 | 4.00 | 460 | 6 | 27 |
| ACM Transactions on Graphics | Q1 | 5.00 | 279 | 3 | 27 |
| Annual Review of Fluid Mechanics | Q1 | 6.00 | 243 | 2 | 4 |
| Light: Science and Applications | Q1 | 4.00 | 193 | 2 | 14 |
| Journal of Fluid Mechanics | Q1 | 1.00 | 281 | 2 | 4 |
| Mathematical Models and Methods in Applied Sciences | Q1 | 1.00 | 103 | 2 | 4 |
| Journal of Open Research Software | Q3 | — | 20 | 2 | 3 |
| Annual Review of Materials Research | Q1 | 3.00 | 195 | 1 | 3 |
Every journal in Computational Mechanics (Q1–Q4) →
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