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20112025
most citedQuantum Computing for Finance: State of the Art and Future Prospects

366 citations

Showing cs.LGShow all

6 papers · 1 filter

cs.LG2023★ 37 cited

FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System

Weizhao Jin, Yuhang Yao, Shanshan Han +5

Federated Learning trains machine learning models on distributed devices by aggregating local model updates instead of local data. However, privacy concerns arise as the aggregated…

cs.LG2020

Neural Ordinary Differential Equation based Recurrent Neural Network Model

Mansura Habiba, Barak A. Pearlmutter

Neural differential equations are a promising new member in the neural network family. They show the potential of differential equations for time series data analysis. In this pape…

cs.LG2018★ 53 cited

Using Deep Learning to Extend the Range of Air-Pollution Monitoring and Forecasting

Philipp Haehnel, Jakub Marecek, Julien Monteil +1

Across numerous applications, forecasting relies on numerical solvers for partial differential equations (PDEs). Although the use of deep-learning techniques has been proposed, act…

cs.LG2018★ 1 cited

Bayesian Classifier for Route Prediction with Markov Chains

Jonathan P. Epperlein, Julien Monteil, Mingming Liu +3

We present here a general framework and a specific algorithm for predicting the destination, route, or more generally a pattern, of an ongoing journey, building on the recent work…

cs.LG2017★ 33 cited

Finding Competitive Network Architectures Within a Day Using UCT

Martin Wistuba

The design of neural network architectures for a new data set is a laborious task which requires human deep learning expertise. In order to make deep learning available for a broad…

cs.LG2015

Electricity Demand Forecasting by Multi-Task Learning

Jean-Baptiste Fiot, Francesco Dinuzzo

We explore the application of kernel-based multi-task learning techniques to forecast the demand of electricity in multiple nodes of a distribution network. We show that recently d…