Comparison overview methods

Please find an overview of the methods submitted below. If you want to propose a another comparison category, please comment below. Also for submitting teams to correct my comparison categorization answers.

	Project	User	Submission tag	RPSS	Visibility	programming language	opportunistic	software	methods	features	CPU vs GPU
1	s2s-ai-challenge-template	jordan.gierschendorf1	submission-methods-7	0.0459475		python	yes	pytorch, hydra	climatology, EMOS, ECMWF CNN and CNN weighting	t2m, tp, orography, week, additionally for ECMWF	GPU
2	s2s-ai-challenge-BSC	lluis.palma	submission-ML_models	0.0288718		python	yes	sklearn	climatology, raw ECWMF, LogisticRegression, RandomForest	t2m, tp	CPU
3	s2s-ai-challenge-uconn	adam.bienkowski	submission-tmp3-0.0.1	0.00620681		python	no	sklearn	RandomForestClassifier	t2m, tp	CPU
4	s2s-ai-challenge-kit-eth-ubern	horatn	submission_local_CNN_final	0.00236371		python	no	tensorflow	CNN	t2m, tp	CPU
5	s2s-ai-challenge-template	damien.specq	submission-damien-specq	0.000467425		R	no	script	Bayesian statistical-dynamical post-processing	t2m, tp	CPU
6	s2s-ai-challenge-ECMWF-internal-testers	chantry.m.j	submission-pplnn-0.0.1	-0.0301027		python	no	tensorflow	CNN, resnet-CNN or Unet	t2m, tp, sp, sst, sm20, tcw, ttr	CPU
7	s2s-ai-challenge-alpin	julius.polz	submission-resubmit-alpine-0.0.1	-0.597942		python	no	tensorflow	Unet	t2m, tp	CPU
8	s2s-ai-challenge-ylabaiers	deepkneko	submission_last	-0.756598		python	no	pytorch	CNN	t2m, tp	GPU
9	s2s-ai-challenge-kjhall01	kjhall01	submission-kyle_nachi_poelm-0.0.6	-0.9918		python	no	XCast using sklearn	Probabilistic Output Extreme Learning Machine (POELM)	t2m, tp	CPU