Results 81 to 90 of about 1,116,663 (238)

Hierarchical Differentiable Fluid Simulation

Computer Graphics Forum, EarlyView.
We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong, Arnaud Schoentgen, Damien Rioux‐Lavoie, Paul G. Kry, Derek Nowrouzezahrai   +4 more
wiley   +1 more source

Adaptive Sampling for BRDF Acquisition

Computer Graphics Forum, EarlyView.
We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi, Saghi Hajisharif, Jonas Unger, Ehsan Miandji   +3 more
wiley   +1 more source

OUGS: Active View Selection via Object‐aware Uncertainty Estimation in 3DGS

Computer Graphics Forum, EarlyView.
Abstract Recent advances in 3D Gaussian Splatting (3DGS) have achieved state‐of‐the‐art results for novel view synthesis. However, efficiently capturing high‐fidelity reconstructions of specific objects within complex scenes remains a significant challenge.
Haiyi Li, Qi Chen, Denis Kalkofen, Hsiang‐Ting Chen   +3 more
wiley   +1 more source

Hyper-Heuristics and Scheduling Problems: Strategies, Application Areas, and Performance Metrics

IEEE Access
Scheduling problems, which involve allocating resources to tasks over specified time periods to optimize objectives, are crucial in various fields. This work presents hyper-heuristic applications for scheduling problems, analyzing 215 peer-reviewed ...
Alonso Vela, Gerardo Humberto Valencia-Rivera, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Ivan Amaya   +4 more
doaj   +1 more source

Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks

IEEE Access, 2020
The development of efficient and effective evolutionary multi-objective optimization (EMO) algorithms has been an active research topic in the evolutionary computation community. Over the years, many EMO algorithms have been proposed.
Lie Meng Pang, Hisao Ishibuchi, Ke Shang
doaj   +1 more source

Interpolated Adaptive Linear Reduced Order Modeling for Deformation Dynamics

Computer Graphics Forum, EarlyView.
Abstract Linear reduced‐order modeling (ROM) is widely used for efficient simulation of deformation dynamics, but its accuracy is often limited by the fixed linearization of the reduced mapping. We propose a new adaptive strategy for linear ROM that allows the reduced mapping to vary dynamically in response to the evolving deformation state ...
Y. Tao, M. Chiaramonte, P. Fernandez
wiley   +1 more source

Edge‐preserving noise for diffusion models

Computer Graphics Forum, EarlyView.
Abstract Classical diffusion models typically rely on isotropic Gaussian noise, treating all regions uniformly and overlooking structural information important for high‐quality generation. We introduce an edge‐preserving diffusion process that generalizes isotropic models via a hybrid noise scheme with an edge‐aware scheduler that smoothly transitions ...
Jente Vandersanden, Sascha Holl, Xingchang Huang, Gurprit Singh   +3 more
wiley   +1 more source

Multi-stage hyper-heuristics for optimisation problems [PDF]

, 2014
There is a growing interest towards self configuring/tuning automated general-purpose reusable heuristic approaches for combinatorial optimisation, such as, hyper-heuristics. Hyper-heuristics are search methodologies which explore the space of heuristics
Kheiri, Ahmed
core  

A runtime analysis of simple hyper-heuristics

, 2013
There is a growing body of work in the field of hyper-heuristics. Hyper-heuristics are high level search methodologies that operate on the space of heuristics to solve hard computational problems.
Lehre, Per Kristian; id_orcid, Ender Özcan, Per Kristian Lehre, Özcan, Ender   +3 more
core   +1 more source

A Unified Framework of Graph-based Evolutionary Multitasking Hyper-heuristic

, 2021
In recent research, hyper-heuristics have attracted increasing attention among researchers in various fields. The most appealing feature of hyper-heuristics is that they aim to provide more generalized solutions to optimization problems by searching in a
Hao, Xingxing, Liu, Jing, Qu, Rong
core   +1 more source