activity
20152021
most citedFlowNet: Learning Optical Flow with Convolutional Networks

604 citations · 813 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV20212 cited

Scene Graph Generation for Better Image Captioning?

Maximilian Mozes, Martin Schmitt, Vladimir Golkov +2

We investigate the incorporation of visual relationships into the task of supervised image caption generation by proposing a model that leverages detected objects and auto-generate…

cs.CV202114 cited

Rotation-Equivariant Deep Learning for Diffusion MRI

Philip Müller, Vladimir Golkov, Valentina Tomassini +1

Convolutional networks are successful, but they have recently been outperformed by new neural networks that are equivariant under rotations and translations. These new networks wor…

eess.AS20206 cited

Speech Synthesis and Control Using Differentiable DSP

Giorgio Fabbro, Vladimir Golkov, Thomas Kemp +1

Modern text-to-speech systems are able to produce natural and high-quality speech, but speech contains factors of variation (e.g. pitch, rhythm, loudness, timbre)\ that text alone…

q-bio.BM20201 cited

Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions

Vladimir Golkov, Alexander Becker, Daniel T. Plop +6

Computer-aided drug discovery is an essential component of modern drug development. Therein, deep learning has become an important tool for rapid screening of billions of molecules…

cs.NE20191 cited

Learning to Evolve

Jan Schuchardt, Vladimir Golkov, Daniel Cremers

Evolution and learning are two of the fundamental mechanisms by which life adapts in order to survive and to transcend limitations. These biological phenomena inspired successful c…

stat.ML2018

q-Space Novelty Detection with Variational Autoencoders

Aleksei Vasilev, Vladimir Golkov, Marc Meissner +5

In machine learning, novelty detection is the task of identifying novel unseen data. During training, only samples from the normal class are available. Test samples are classified…