Saved in:
| Main Authors: | Lim, Hansol, Lee, Jee Won, Boyack, Jonathan, Choi, Jongseong Brad |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.14691 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
VEGA: Electric Vehicle Navigation Agent via Physics-Informed Neural Operator and Proximal Policy Optimization
by: Lim, Hansol, et al.
Published: (2025)
by: Lim, Hansol, et al.
Published: (2025)
A Hybrid Surrogate for Electric Vehicle Parameter Estimation and Power Consumption via Physics-Informed Neural Operators
by: Lim, Hansol, et al.
Published: (2025)
by: Lim, Hansol, et al.
Published: (2025)
Micro-splatting: Multistage Isotropy-informed Covariance Regularization Optimization for High-Fidelity 3D Gaussian Splatting
by: Lee, Jee Won, et al.
Published: (2025)
by: Lee, Jee Won, et al.
Published: (2025)
Hybrid Vision Servoing with Depp Alignment and GRU-Based Occlusion Recovery
by: Lee, Jee Won, et al.
Published: (2025)
by: Lee, Jee Won, et al.
Published: (2025)
VISKY: Virtual Inertia Skyhook Control for Semi-Active Suspension Systems Using Magnetorheological Dampers
by: Lim, Hansol, et al.
Published: (2025)
by: Lim, Hansol, et al.
Published: (2025)
Splat2Real: Novel-view Scaling for Physical AI with 3D Gaussian Splatting
by: Lim, Hansol, et al.
Published: (2026)
by: Lim, Hansol, et al.
Published: (2026)
MATT-GS: Masked Attention-based 3DGS for Robot Perception and Object Detection
by: Lee, Jee Won, et al.
Published: (2025)
by: Lee, Jee Won, et al.
Published: (2025)
SARA: Scene-Aware Reconstruction Accelerator
by: Lee, Jee Won, et al.
Published: (2026)
by: Lee, Jee Won, et al.
Published: (2026)
LiteVoxel: Low-memory Intelligent Thresholding for Efficient Voxel Rasterization
by: Lee, Jee Won, et al.
Published: (2025)
by: Lee, Jee Won, et al.
Published: (2025)
Transforming Omnidirectional RGB-LiDAR data into 3D Gaussian Splatting
by: Bae, Semin, et al.
Published: (2026)
by: Bae, Semin, et al.
Published: (2026)
PRISM: Color-Stratified Point Cloud Sampling
by: Lim, Hansol, et al.
Published: (2026)
by: Lim, Hansol, et al.
Published: (2026)
RoPINN: Region Optimized Physics-Informed Neural Networks
by: Wu, Haixu, et al.
Published: (2024)
by: Wu, Haixu, et al.
Published: (2024)
ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
by: Wu, Haixu, et al.
Published: (2025)
by: Wu, Haixu, et al.
Published: (2025)
Damper-B-PINN: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Vehicle State Estimation
by: Zeng, Tianyi, et al.
Published: (2025)
by: Zeng, Tianyi, et al.
Published: (2025)
PINN-Obs: Physics-Informed Neural Network-Based Observer for Nonlinear Dynamical Systems
by: Farkane, Ayoub, et al.
Published: (2025)
by: Farkane, Ayoub, et al.
Published: (2025)
RBF-PINN: Non-Fourier Positional Embedding in Physics-Informed Neural Networks
by: Zeng, Chengxi, et al.
Published: (2024)
by: Zeng, Chengxi, et al.
Published: (2024)
Pathwise Explanation of ReLU Neural Networks
by: Lim, Seongwoo, et al.
Published: (2025)
by: Lim, Seongwoo, et al.
Published: (2025)
TIDI-GS: Floater Suppression in 3D Gaussian Splatting for Enhanced Indoor Scene Fidelity
by: Yang, Sooyeun, et al.
Published: (2026)
by: Yang, Sooyeun, et al.
Published: (2026)
LiDAR-3DGS: LiDAR Reinforced 3D Gaussian Splatting for Multimodal Radiance Field Rendering
by: Lim, Hansol, et al.
Published: (2024)
by: Lim, Hansol, et al.
Published: (2024)
SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks
by: Anticev, John, et al.
Published: (2024)
by: Anticev, John, et al.
Published: (2024)
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks
by: Phan-Trong, Dat, et al.
Published: (2024)
by: Phan-Trong, Dat, et al.
Published: (2024)
A Physics Informed Neural Network (PINN) Methodology for Coupled Moving Boundary PDEs
by: Kathane, Shivprasad, et al.
Published: (2024)
by: Kathane, Shivprasad, et al.
Published: (2024)
MP-PINN: A Multi-Phase Physics-Informed Neural Network for Epidemic Forecasting
by: Nguyen, Thang, et al.
Published: (2024)
by: Nguyen, Thang, et al.
Published: (2024)
$PINN - a Domain Decomposition Method for Bayesian Physics-Informed Neural Networks
by: Figueres, Júlia Vicens, et al.
Published: (2025)
by: Figueres, Júlia Vicens, et al.
Published: (2025)
naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement
by: Kim, Hankyeol, et al.
Published: (2026)
by: Kim, Hankyeol, et al.
Published: (2026)
PINN-FEM: A Hybrid Approach for Enforcing Dirichlet Boundary Conditions in Physics-Informed Neural Networks
by: Sobh, Nahil, et al.
Published: (2025)
by: Sobh, Nahil, et al.
Published: (2025)
Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunities
by: Wong, Jian Cheng, et al.
Published: (2025)
by: Wong, Jian Cheng, et al.
Published: (2025)
Spectral Informed Neural Network: An Efficient and Low-Memory PINN
by: Yu, Tianchi, et al.
Published: (2024)
by: Yu, Tianchi, et al.
Published: (2024)
MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries
by: Zhang, Weizheng, et al.
Published: (2026)
by: Zhang, Weizheng, et al.
Published: (2026)
Finite-PINN: A Physics-Informed Neural Network with Finite Geometric Encoding for Solid Mechanics
by: Li, Haolin, et al.
Published: (2024)
by: Li, Haolin, et al.
Published: (2024)
Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction
by: Chiu, Pao-Hsiung, et al.
Published: (2026)
by: Chiu, Pao-Hsiung, et al.
Published: (2026)
Direct Estimation of Porosity from Seismic Data using Rock and Wave Physics Informed Neural Networks (RW-PINN)
by: Vashisth, Divakar, et al.
Published: (2022)
by: Vashisth, Divakar, et al.
Published: (2022)
How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks
by: Lim, Dong-Won
Published: (2026)
by: Lim, Dong-Won
Published: (2026)
AL-PINN: Active Learning-Driven Physics-Informed Neural Networks for Efficient Sample Selection in Solving Partial Differential Equations
by: Park, Keon Vin
Published: (2025)
by: Park, Keon Vin
Published: (2025)
Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction
by: Bazgir, Omid, et al.
Published: (2023)
by: Bazgir, Omid, et al.
Published: (2023)
Gradient Enhanced Self-Training Physics-Informed Neural Network (gST-PINN) for Solving Nonlinear Partial Differential Equations
by: Iyer, Narayan S, et al.
Published: (2025)
by: Iyer, Narayan S, et al.
Published: (2025)
WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs with Physics-Informed Neural Networks
by: Walter, Linus, et al.
Published: (2025)
by: Walter, Linus, et al.
Published: (2025)
Fatigue-PINN: Physics-Informed Fatigue-Driven Motion Modulation and Synthesis
by: Loi, Iliana, et al.
Published: (2025)
by: Loi, Iliana, et al.
Published: (2025)
Lang-PINN: From Language to Physics-Informed Neural Networks via a Multi-Agent Framework
by: He, Xin, et al.
Published: (2025)
by: He, Xin, et al.
Published: (2025)
xLSTM-PINN: Memory-Gated Spectral Remodeling for Physics-Informed Learning
by: Tao, Ze, et al.
Published: (2025)
by: Tao, Ze, et al.
Published: (2025)
Similar Items
-
VEGA: Electric Vehicle Navigation Agent via Physics-Informed Neural Operator and Proximal Policy Optimization
by: Lim, Hansol, et al.
Published: (2025) -
A Hybrid Surrogate for Electric Vehicle Parameter Estimation and Power Consumption via Physics-Informed Neural Operators
by: Lim, Hansol, et al.
Published: (2025) -
Micro-splatting: Multistage Isotropy-informed Covariance Regularization Optimization for High-Fidelity 3D Gaussian Splatting
by: Lee, Jee Won, et al.
Published: (2025) -
Hybrid Vision Servoing with Depp Alignment and GRU-Based Occlusion Recovery
by: Lee, Jee Won, et al.
Published: (2025) -
VISKY: Virtual Inertia Skyhook Control for Semi-Active Suspension Systems Using Magnetorheological Dampers
by: Lim, Hansol, et al.
Published: (2025)