Hothker, A.
Standard Author Listing
with: Eyben, F.: Being bored? Recognising natural interest by extensive audi...
with: Gast, J.: Being bored? Recognising natural interest by extensive audio...
with: Hornler, B.: Being bored? Recognising natural interest by extensive au...
with: Konosu, H.: Being bored? Recognising natural interest by extensive aud...
with: Muller, R.: Being bored? Recognising natural interest by extensive aud...
with: Rigoll, G.: Being bored? Recognising natural interest by extensive aud...
with: Schuller, B.: Being bored? Recognising natural interest by extensive a...
with: Wollmer, M.: Being bored? Recognising natural interest by extensive au...
8 for Hothker, A.
Hotho, A.
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with: Baumhauer, R.: Semi-supervised Learning for Grain Size Distribution In...
with: Dulny, A.: Do Different Deep Metric Learning Losses Lead to Similar Le...
with: Kobs, K.: Do Different Deep Metric Learning Losses Lead to Similar Lea...
with: Kobs, K.: InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for...
with: Kobs, K.: Self-Supervised Multi-Task Pretraining Improves Image Aesthe...
with: Kobs, K.: Semi-supervised Learning for Grain Size Distribution Interpo...
with: Krause, A.: Semi-supervised Learning for Grain Size Distribution Inter...
with: Paeth, H.: Semi-supervised Learning for Grain Size Distribution Interp...
with: Pfister, J.: Self-Supervised Multi-Task Pretraining Improves Image Aes...
with: Schafer, C.: Semi-supervised Learning for Grain Size Distribution Inte...
with: Steininger, M.: Do Different Deep Metric Learning Losses Lead to Simil...
with: Steininger, M.: InDiReCT: Language-Guided Zero-Shot Deep Metric Learni...
with: Steininger, M.: Semi-supervised Learning for Grain Size Distribution I...
13 for Hotho, A.
Hothorn, T.
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with: Durr, O.: Deep and interpretable regression models for ordinal outcomes
with: Herzog, L.: Deep and interpretable regression models for ordinal outco...
with: Kook, L.: Deep and interpretable regression models for ordinal outcomes
with: Lausen, B.: Double-bagging: combining classifiers by bootstrap aggrega...
with: Sick, B.: Deep and interpretable regression models for ordinal outcomes