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Found 13 papers, 3 papers with code
Pareto Set Learning for Neural Multi-objective Combinatorial Optimization
In this work, we generalize the idea of neural combinatorial optimization, and develop a learning-based approach to approximate the whole Pareto set for a given MOCO problem without further search procedure.
Template NeRF: Towards Modeling Dense Shape Correspondences from Category-Specific Object Images
By representing object instances within the same category as shape and appearance variation of a shared NeRF template, our proposed method can achieve dense shape correspondences reasoning on images for a wide range of object classes.
Preference Conditioned Neural Multi-objective Combinatorial Optimization
In this work, we generalize the idea of neural combinatorial optimization, and develop a learning-based approach to approximate the whole Pareto set for a given MOCO problem without further search procedure.
Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles
We call such a mobility market with AV renting options the "AV crowdsourcing market".
A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems with Renewables
The increasing uncertainty level caused by growing renewable energy sources (RES) and aging transmission networks poses a great challenge in the assessment of total transfer capability (TTC) and available transfer capability (ATC).
Superconductor-metal quantum transition at the EuO-KTaO3 interface
Superconductivity has been one of the most fascinating quantum states of matter for over several decades.
Superconductivity Mesoscale and Nanoscale Physics Materials Science
Controllable Pareto Multi-Task Learning
With a fixed model capacity, the tasks would be conflicted with each other, and the system usually has to make a trade-off among learning all of them together.
Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach
Multi-vehicle routing problem with soft time windows (MVRPSTW) is an indispensable constituent in urban logistics distribution systems.
Pareto Multi-Task Learning
Recently, a novel method is proposed to find one single Pareto optimal solution with good trade-off among different tasks by casting multi-task learning as multiobjective optimization.
A Keyframe-based Continuous Visual SLAM for RGB-D Cameras via Nonparametric Joint Geometric and Appearance Representation
The experimental evaluations using publicly available RGB-D benchmarks show that the developed keyframe selection technique using continuous visual odometry outperforms its robust dense (and direct) visual odometry equivalent.
Nonlinear Collaborative Scheme for Deep Neural Networks
Different from them, in this paper, we aim to link the generalization ability of a deep network to optimizing a new objective function.
A Batched Scalable Multi-Objective Bayesian Optimization Algorithm
The proposed algorithm uses the Bayesian neural network as the scalable surrogate model.
Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism
Multistep traffic forecasting on road networks is a crucial task in successful intelligent transportation system applications.
