gwmodeling / challenge Goto Github PK

Please open a GitHub Issue to register your team.

Model: XX-model
Names: X.X. XYZ

Model: Hybrid deep-learning
Members

1. Sivarama Krishna Reddy Chidepudi
2. Abel Henriot
3. Nicolas Massei
4. Abderrahim Jardani

Im sure Im missing something but the forcing data csv files are constant in time - just one value for all times. Is that right? Like I said Im slow so maybe Im not understanding something...

Model: LSTM
Names: Max Rudolph, Alireza Kavousi (both Institute of Groundwater Management, TU Dresden, Germany)

Model: LSTM
Names: Raphael Schneider & Julian Koch

Discussed in #34

Model: Transformer
Member: Anna Pölz, Ali Obeid, Ahmad Ameen

Model: LSTM

Members:
Morteza Behbooei
Jimmy Lin
Rojin Meysami

Model: NHiTS
Names: Nikolas Benavides Höglund

I'm a bit late to the game, but I would like to give it a chance and provide a contribution for this challenge. The model I'm using is an implementation of NHiTS (link to paper). LUHG = Lund University HydroGeology.

Model: Random forest ensemble
Name: Antoine Di Ciacca

Model: Ensemble of shallow learners
Names:

• Max Nölscher

team members: Ed de Sousa, Rui Hugman, Mike Fienen, Nick Martin, Jeremy White
approach: ensemble of TFN models

Geological Survey of Sweden

Model: SGU-HYPE
Names: Anders Retzner

The model is based on the HYPE model (http://www.smhi.net/hype/wiki/doku.php?id=start) but with some added processes to improve groundwater level predictions.

@selinawaang registering the team here.

Model: Linear Regression with Distributed Lags
Member: Jonathan Kennel

Model: multi-frequency LSTM with MC dropout for uncertainty estimates
Names: Tim Franken

Note: I'm a bit late with my subscription but still plan / hope to get the submission in before the deadline (5/1, 24hCET) if that's ok

Hello,

I'm planning to have a crack at this.

Matthew Taylor

Model: Mixed Effects Random Forest (MERF)
Names: Ayush Prasad (University of Helsinki)

Hi,

I just submitted my results for the challenge and submitted my results.

Model: 1D-CNN Deeplearning model
Team: AmirEtAl
please check and confirm if you have recieved.

Best,
Amir,

Model: HydroSight - lumped conceptual model
Names: Xinyang Fan, Tim Peterson

Model: Random Forest model
Name: Jānis Bikše

I worked on this some time ago and was slow to polish it, but just noticed that Team Mirkwood has quite a similar approach. I hope it won't make any problems but definitely, it would interesting to compare the results.