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07/26/2023
Reinforced Potential Field for Multi-Robot Motion Planning in Cluttered Environments
Motion planning is challenging for multiple robots in cluttered environm...
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06/08/2023
Motion Planning for Aerial Pick-and-Place based on Geometric Feasibility Constraints
This paper studies the motion planning problem of the pick-and-place of ...
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05/12/2023
Uncertainty Estimation for Deep Learning Image Reconstruction using a Local Lipschitz Metric
The use of deep learning approaches for image reconstruction is of conte...
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04/20/2023
Learning Neural Duplex Radiance Fields for Real-Time View Synthesis
Neural radiance fields (NeRFs) enable novel view synthesis with unpreced...
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03/10/2023
Neural Partial Differential Equations with Functional Convolution
We present a lightweighted neural PDE representation to discover the hid...
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12/07/2022
FSID: Fully Synthetic Image Denoising via Procedural Scene Generation
For low-level computer vision and image processing ML tasks, training on...
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12/07/2022
Policy Transfer via Enhanced Action Space
Though transfer learning is promising to increase the learning efficienc...
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09/22/2022
Fluidic Topology Optimization with an Anisotropic Mixture Model
Fluidic devices are crucial components in many industrial applications i...
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09/04/2022
Symplectically Integrated Symbolic Regression of Hamiltonian Dynamical Systems
Here we present Symplectically Integrated Symbolic Regression (SISR), a ...
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04/21/2022
Cellular Topology Optimization on Differentiable Voronoi Diagrams
Cellular structures manifest their outstanding mechanical properties in ...
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03/15/2022
Learning Spatio-Temporal Downsampling for Effective Video Upscaling
Downsampling is one of the most basic image processing operations. Impro...
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02/10/2022
On Real-time Image Reconstruction with Neural Networks for MRI-guided Radiotherapy
MRI-guidance techniques that dynamically adapt radiation beams to follow...
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05/18/2021
Solid-Fluid Interaction with Surface-Tension-Dominant Contact
We propose a novel three-way coupling method to model the contact intera...
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05/17/2021
Thin-Film Smoothed Particle Hydrodynamics Fluid
We propose a particle-based method to simulate thin-film fluid that join...
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10/23/2020
Nonseparable Symplectic Neural Networks
Predicting the behaviors of Hamiltonian systems has been drawing increas...
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08/18/2020
Soft Multicopter Control using Neural Dynamics Identification
Dynamic control of a soft-body robot to deliver complex behaviors with l...
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06/23/2020
Learning Physical Constraints with Neural Projections
We propose a new family of neural networks to predict the behaviors of p...
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06/07/2020
RoeNets: Predicting Discontinuity of Hyperbolic Systems from Continuous Data
We introduce Roe Neural Networks (RoeNets) that can predict the disconti...
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06/07/2020
Neural Vortex Method: from Finite Lagrangian Particles to Infinite Dimensional Eulerian Dynamics
In the field of fluid numerical analysis, there has been a long-standing...
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05/11/2020
Symplectic Neural Networks in Taylor Series Form for Hamiltonian Systems
We propose an effective and light-weighted learning algorithm, Symplecti...
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03/02/2020
A Hybrid Lagrangian-Eulerian Method for Topology Optimization
We propose LETO, a new hybrid Lagrangian-Eulerian method for topology op...
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02/01/2020
AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud Processing
This paper presents a novel physics-inspired deep learning approach for ...
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06/20/2019
PuzzleFlex: kinematic motion of chains with loose joints
This paper presents a method of computing free motions of a planar assem...
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10/15/2017
Deep Learning for Rapid Sparse MR Fingerprinting Reconstruction
PURPOSE: Demonstrate a novel fast method for reconstruction of multi-dim...
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06/10/2017
