Management
766 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Management
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Libraries
Use these libraries to find Management models and implementations
BIG-bench
Most implemented papers
A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
They are, along with a number of recently reviewed or published portfolio-selection strategies, examined in three back-test experiments with a trading period of 30 minutes in a cryptocurrency market.
T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
lehaifeng/T-GCN
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However, traffic forecasting has always been considered an open scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change with time, namely, spatial dependence and temporal dependence.
The Case for Learned Index Structures
Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not.
Leveraging BERT for Extractive Text Summarization on Lectures
This paper reports on the project called Lecture Summarization Service, a python based RESTful service that utilizes the BERT model for text embeddings and KMeans clustering to identify sentences closes to the centroid for summary selection.
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning
In this study, we present a severity score prediction model for COVID-19 pneumonia for frontal chest X-ray images.
COVID-19 Image Data Collection: Prospective Predictions Are the Future
ieee8023/covid-chestxray-dataset
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This dataset currently contains hundreds of frontal view X-rays and is the largest public resource for COVID-19 image and prognostic data, making it a necessary resource to develop and evaluate tools to aid in the treatment of COVID-19.
Deep Reinforcement Learning
google/dopamine
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We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources.
The Plant Pathology 2020 challenge dataset to classify foliar disease of apples
Boyiliee/SITT
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Appropriate and timely deployment of disease management depends on early disease detection.
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
The aggregation is further combined with external factors, such as weather and day of the week, to predict the final traffic of crowds in each and every region.
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
facebookresearch/TensorComprehensions
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Deep learning models with convolutional and recurrent networks are now ubiquitous and analyze massive amounts of audio, image, video, text and graph data, with applications in automatic translation, speech-to-text, scene understanding, ranking user preferences, ad placement, etc.
