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J. Dabrowski

16 papers hereh-index 13493 citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author10
  • middle author6

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG10
  • stat.AP4
  • cs.RO1
  • stat.ML1
same name
  • J. Dabrowski — 9 papers, h 18
  • J. Dabrowski — 1 paper, h 21

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedBayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires

43 citations · 122 across the 16 of their papers we have counts for

collaborators
Showing 2020 · cs.LGShow all

3 papers · 2 filters

cs.LG2020

Deep Learning and Statistical Models for Time-Critical Pedestrian Behaviour Prediction

Joel Janek Dabrowski, Johan Pieter de Villiers, Ashfaqur Rahman +1

The time it takes for a classifier to make an accurate prediction can be crucial in many behaviour recognition problems. For example, an autonomous vehicle should detect hazardous…

cs.LG2020★ 11 cited

Sequence-to-Sequence Imputation of Missing Sensor Data

Joel Janek Dabrowski, Ashfaqur Rahman

Although the sequence-to-sequence (encoder-decoder) model is considered the state-of-the-art in deep learning sequence models, there is little research into using this model for re…

cs.LG2020★ 26 cited

ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting

Joel Janek Dabrowski, YiFan Zhang, Ashfaqur Rahman

Recurrent and convolutional neural networks are the most common architectures used for time series forecasting in deep learning literature. These networks use parameter sharing by…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.