SOTAVerified

Physical Simulations

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 100 papers

TitleStatusHype
DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interaction—0
DiffAvatar: Simulation-Ready Garment Optimization with Differentiable Simulation—0
Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives—0
Discovering Interpretable Physical Models using Symbolic Regression and Discrete Exterior Calculus—0
Efficient nonlinear manifold reduced order model—0
Exploring Physical Latent Spaces for High-Resolution Flow Restoration—0
Frequency-aware Interface Dynamics with Generative Adversarial Networks—0
Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations—0
Generalizing Graph ODE for Learning Complex System Dynamics across Environments—0
Grounding Creativity in Physics: A Brief Survey of Physical Priors in AIGC—0
In-Distribution Interpretability for Challenging Modalities—0
`Just One More Sensor is Enough' -- Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors—0
Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks—0
Learnable & Interpretable Model Combination in Dynamical Systems Modeling—0
Local Geometric Indexing of High Resolution Data for Facial Reconstruction from Sparse Markers—0
ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design)—0
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature—0
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions—0
Multi-Physics Simulations via Coupled Fourier Neural Operator—0
Neural Posterior Estimation with Differentiable Simulators—0
NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design—0
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods—0
Phys4DGen: A Physics-Driven Framework for Controllable and Efficient 4D Content Generation from a Single Image—0
PhysicsGen: Can Generative Models Learn from Images to Predict Complex Physical Relations?—0
Predicting Natural Hazards with Neuronal Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HOOD_OuterChamfer (cm)5.36—Unverified
2PBNS_DressChamfer (cm)4.87—Unverified
3PBNS_OuterChamfer (cm)4.86—Unverified
4NCS_OuterChamfer (cm)4.74—Unverified
5NCS_DressChamfer (cm)4.55—Unverified
6HOOD_DressChamfer (cm)4.29—Unverified
7PBNS_UpperChamfer (cm)2.69—Unverified
8HOOD_UpperChamfer (cm)2.67—Unverified
9NCS_UpperChamfer (cm)2.11—Unverified
10HOOD_LowerChamfer (cm)2.07—Unverified