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Found 14 papers, 5 papers with code
Exploiting Spatial-Temporal Semantic Consistency for Video Scene Parsing
Compared with image scene parsing, video scene parsing introduces temporal information, which can effectively improve the consistency and accuracy of prediction.
Pure Characteristics Demand Models and Distributionally Robust Mathematical Programs with Stochastic Complementarity Constraints
We formulate pure characteristics demand models under uncertainties of probability distributions as distributionally robust mathematical programs with stochastic complementarity constraints (DRMP-SCC).
Optimization and Control 90C15, 90C33, 90C26
New gedanken experiment on higher-dimensional asymptotically AdS Reissner-Nordström black hole
Viewing the negative cosmological constant as a dynamical quantity derived from the matter field, we study the weak cosmic censorship conjecture for the higher-dimensional asymptotically AdS Reissner-Nordstr\"om black hole.
General Relativity and Quantum Cosmology High Energy Physics - Theory
Scene Segmentation with Dual Relation-aware Attention Network
We conduct extensive experiments to validate the effectiveness of our network and achieve new state-of-the-art segmentation performance on four challenging scene segmentation data sets, i. e., Cityscapes, ADE20K, PASCAL Context, and COCO Stuff data sets.
Ranked #6 on
Semantic Segmentation
on COCO-Stuff test
The Joint Automated Repository for Various Integrated Simulations (JARVIS) for data-driven materials design
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques.
Materials Science Computational Physics
Non-Autoregressive Image Captioning with Counterfactuals-Critical Multi-Agent Learning
In this paper, we propose a Non-Autoregressive Image Captioning (NAIC) model with a novel training paradigm: Counterfactuals-critical Multi-Agent Learning (CMAL).
KACC: A Multi-task Benchmark for Knowledge Abstraction, Concretization and Completion
Based on the datasets, we propose novel tasks such as multi-hop knowledge abstraction (MKA), multi-hop knowledge concretization (MKC) and then design a comprehensive benchmark.
AHash: A Load-Balanced One Permutation Hash
Unlike the densification to fill the empty bins after they undesirably occur, our design goal is to balance the load so as to reduce the empty bins in advance.
X-Forest: Approximate Random Projection Trees for Similarity Measurement
First, we introduced RP Trees into the tasks of similarity measurement such that accuracy is improved.
Static charged dilaton black hole cannot be overcharged by gedanken experiments
We consider the new version of the gedanken experiments proposed recently by Sorce and Wald to overcharge a static charged dilaton black hole.
High Energy Physics - Theory
Deep Learning Based Energy Disaggregation and On/Off Detection of Household Appliances
On the basis of energy disaggregation, we then investigate the performance of two deep-learning based frameworks for the task of on/off detection which aims at estimating whether an appliance is in operation or not.
DENet: A Universal Network for Counting Crowd with Varying Densities and Scales
Counting people or objects with significantly varying scales and densities has attracted much interest from the research community and yet it remains an open problem.
Accelerated Discovery of Efficient Solar-cell Materials using Quantum and Machine-learning Methods
Solar-energy plays an important role in solving serious environmental problems and meeting high-energy demand.
Materials Science
Machine Translation for Subtitling: A Large-Scale Evaluation
This article describes a large-scale evaluation of the use of Statistical Machine Translation for professional subtitling.
