activity
20172022
most citedDefining a synthetic data generator for realistic electric vehicle charging sessions

14 citations · 28 across the 4 of their papers we have counts for

collaborators

11 papers

cs.AI20221 cited

Computationally efficient joint coordination of multiple electric vehicle charging points using reinforcement learning

Manu Lahariya, Nasrin Sadeghianpourhamami, Chris Develder

A major challenge in todays power grid is to manage the increasing load from electric vehicle (EV) charging. Demand response (DR) solutions aim to exploit flexibility therein, i.e.…

cs.AI20228 cited

Optimized cost function for demand response coordination of multiple EV charging stations using reinforcement learning

Manu Lahariya, Nasrin Sadeghianpourhamami, Chris Develder

Electric vehicle (EV) charging stations represent a substantial load with significant flexibility. The exploitation of that flexibility in demand response (DR) algorithms becomes i…

cs.OH202214 cited

Defining a synthetic data generator for realistic electric vehicle charging sessions

Manu Lahariya, Dries Benoit, Chris Develder

Electric vehicle (EV) charging stations have become prominent in electricity grids in the past years. Analysis of EV charging sessions is useful for flexibility analysis, load bala…

cs.CL2020

DWIE: an entity-centric dataset for multi-task document-level information extraction

Klim Zaporojets, Johannes Deleu, Chris Develder +1

This paper presents DWIE, the 'Deutsche Welle corpus for Information Extraction', a newly created multi-task dataset that combines four main Information Extraction (IE) annotation…

cs.CL2020

Solving Arithmetic Word Problems by Scoring Equations with Recursive Neural Networks

Klim Zaporojets, Giannis Bekoulis, Johannes Deleu +2

Solving arithmetic word problems is a cornerstone task in assessing language understanding and reasoning capabilities in NLP systems. Recent works use automatic extraction and rank…

cs.CL20195 cited

Sub-event detection from Twitter streams as a sequence labeling problem

Giannis Bekoulis, Johannes Deleu, Thomas Demeester +1

This paper introduces improved methods for sub-event detection in social media streams, by applying neural sequence models not only on the level of individual posts, but also direc…