Mixture-of-experts VAEs can disregard variation in surjective multimodal data

no code implementations • 11 Apr 2022 • Jannik Wolff, Tassilo Klein, Moin Nabi, Rahul G. Krishnan, Shinichi Nakajima

Machine learning systems are often deployed in domains that entail data from multiple modalities, for example, phenotypic and genotypic characteristics describe patients in healthcare.

Hierarchical Multimodal Variational Autoencoders

no code implementations • 29 Sep 2021 • Jannik Wolff, Rahul G Krishnan, Lukas Ruff, Jan Nikolas Morshuis, Tassilo Klein, Shinichi Nakajima, Moin Nabi

Humans find structure in natural phenomena by absorbing stimuli from multiple input sources such as vision, text, and speech.

Learning Graph-Based Priors for Generalized Zero-Shot Learning

no code implementations • 22 Oct 2020 • Colin Samplawski, Jannik Wolff, Tassilo Klein, Moin Nabi

The task of zero-shot learning (ZSL) requires correctly predicting the label of samples from classes which were unseen at training time.

Generalized Zero-Shot Learning Word Embeddings

Low-Shot Learning from Imaginary 3D Model

no code implementations • 4 Jan 2019 • Frederik Pahde, Mihai Puscas, Jannik Wolff, Tassilo Klein, Nicu Sebe, Moin Nabi

Since the advent of deep learning, neural networks have demonstrated remarkable results in many visual recognition tasks, constantly pushing the limits.

Few-Shot Learning