Vladimir Golkov

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 19

Top Topics

Virtual Screening

Amino Acid Residues

Speech Synthesis

Top Venues

Bildverarbeitung für die Medizin

IEEE Trans. Medical Imaging

Publications

Moritz Zaiss, Junaid R. Rajput, Hoai Nam Dang, Vladimir Golkov, Daniel Cremers, Florian Knoll, Andreas K. Maier
Exploring GPT-4 as MR Sequence and Reconstruction Programming Assistant - GPT4MR. Bildverarbeitung für die Medizin (2024)
Fabian Bongratz, Vladimir Golkov, Lukas Mautner, Luca Della Libera, Frederik Heetmeyer, Felix Czaja, Julian Rodemann, Daniel Cremers
How to Choose a Reinforcement-Learning Algorithm. CoRR (2024)
Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer, Daniel Cremers, Andreas K. Maier, Moritz Zaiss
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution. CoRR (2023)
Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang, Moritz Zaiss, Andreas Maier, Daniel Cremers
Scale-Equivariant Deep Learning for 3D Data. CoRR (2023)
Philip Müller, Vladimir Golkov, Valentina Tomassini, Daniel Cremers
Rotation-Equivariant Deep Learning for Diffusion MRI. CoRR (2021)
Maximilian Mozes, Martin Schmitt, Vladimir Golkov, Hinrich Schütze, Daniel Cremers
Scene Graph Generation for Better Image Captioning? CoRR (2021)
Giorgio Fabbro, Vladimir Golkov, Thomas Kemp, Daniel Cremers
Speech Synthesis and Control Using Differentiable DSP. CoRR (2020)
Vladimir Golkov, Alexander Becker, Daniel T. Plop, Daniel Cuturilo, Neda Davoudi, Jeffrey L. Mendenhall, Rocco Moretti, Jens Meiler, Daniel Cremers
Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions. CoRR (2020)
Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers
3D Deep Learning for Biological Function Prediction from Physical Fields. 3DV (2020)
Luca Della Libera, Vladimir Golkov, Yue Zhu, Arman Mielke, Daniel Cremers
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods. CoRR (2019)
Jan Schuchardt, Vladimir Golkov, Daniel Cremers
Learning to Evolve. CoRR (2019)
Aleksei Vasilev, Vladimir Golkov, Ilona Lipp, Eleonora Sgarlata, Valentina Tomassini, Derek K. Jones, Daniel Cremers
q-Space Novelty Detection with Variational Autoencoders. CoRR (2018)
Elie Aljalbout, Vladimir Golkov, Yawar Siddiqui, Daniel Cremers
Clustering with Deep Learning: Taxonomy and New Methods. CoRR (2018)
Philip Häusser, Johannes Plapp, Vladimir Golkov, Elie Aljalbout, Daniel Cremers
Associative Deep Clustering: Training a Classification Network with No Labels. GCPR (2018)
Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers
3D Deep Learning for Biological Function Prediction from Physical Fields. CoRR (2017)
Jan Kukacka, Vladimir Golkov, Daniel Cremers
Regularization for Deep Learning: A Taxonomy. CoRR (2017)
Vladimir Golkov, Alexey Dosovitskiy, Jonathan I. Sperl, Marion I. Menzel, Michael Czisch, Philipp G. Sämann, Thomas Brox, Daniel Cremers
q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans. IEEE Trans. Medical Imaging 35 (5) (2016)
Vladimir Golkov, Tim Sprenger, Jonathan Sperl, Marion I. Menzel, Michael Czisch, Philipp G. Sämann, Daniel Cremers
Model-free novelty-based diffusion MRI. ISBI (2016)
Vladimir Golkov, Marcin J. Skwark, Antonij Golkov, Alexey Dosovitskiy, Thomas Brox, Jens Meiler, Daniel Cremers
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images. NIPS (2016)
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox
FlowNet: Learning Optical Flow with Convolutional Networks. ICCV (2015)
Vladimir Golkov, Alexey Dosovitskiy, Philipp G. Sämann, Jonathan I. Sperl, Tim Sprenger, Michael Czisch, Marion I. Menzel, Pedro A. Gómez, Axel Haase, Thomas Brox, Daniel Cremers
q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans. MICCAI (1) (2015)
Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox
FlowNet: Learning Optical Flow with Convolutional Networks. CoRR (2015)