7 citations · 31 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning to Taste: A Multimodal Wine Dataset
Thoranna Bender, Simon Moe Sørensen, Alireza Kashani +5
We present WineSensed, a large multimodal wine dataset for studying the relations between visual perception, language, and flavor. The dataset encompasses 897k images of wine label…
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval
Frederik Warburg, Marco Miani, Silas Brack +1
We propose the first Bayesian encoder for metric learning. Rather than relying on neural amortization as done in prior works, we learn a distribution over the network weights with…
Laplacian Autoencoders for Learning Stochastic Representations
Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz +2
Established methods for unsupervised representation learning such as variational autoencoders produce none or poorly calibrated uncertainty estimates making it difficult to evaluat…
Probabilistic Spatial Transformer Networks
Pola Schwöbel, Frederik Warburg, Martin Jørgensen +2
Spatial Transformer Networks (STNs) estimate image transformations that can improve downstream tasks by `zooming in' on relevant regions in an image. However, STNs are hard to trai…