Fred A. Hamprecht

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 68

Top Venues

Publications

Lennart Bürger, Fred A. Hamprecht, Boaz Nadler
Truth is Universal: Robust Detection of Lies in LLMs. CoRR (2024)
Enrique Fita Sanmartín, Christoph Schnörr, Fred A. Hamprecht
The Central Spanning Tree Problem. CoRR (2024)
Peter Lippmann, Gerrit Gerhartz, Roman Remme, Fred A. Hamprecht
Tensor Frames - How To Make Any Message Passing Network Equivariant. CoRR (2024)
Moritz Sturm, Lorenzo Cerrone, Fred A. Hamprecht
SynCellFactory: Generative Data Augmentation for Cell Tracking. CoRR (2024)
Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht, Dmitry Kobak
From $t$-SNE to UMAP with contrastive learning. ICLR (2023)
Philipp Nazari, Sebastian Damrich, Fred A. Hamprecht
Geometric Autoencoders - What You See is What You Decode. CoRR (2023)
Philipp Nazari, Sebastian Damrich, Fred A. Hamprecht
Geometric Autoencoders - What You See is What You Decode. ICML (2023)
Roman Remme, Tobias Kaczun, Maximilian Scheurer, Andreas Dreuw, Fred A. Hamprecht
KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory. CoRR (2023)
Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht, Dmitry Kobak
Contrastive learning unifies t-SNE and UMAP. CoRR (2022)
Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht
Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources. NeurIPS (2022)
Alberto Bailoni, Constantin Pape, Nathan Hütsch, Steffen Wolf, Thorsten Beier, Anna Kreshuk, Fred A. Hamprecht
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation. CVPR (2022)
Lorenzo Cerrone, Athul Vijayan, Tejasvinee Mody, Kay Schneitz, Fred A. Hamprecht
CellTypeGraph: A New Geometric Computer Vision Benchmark. CoRR (2022)
Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht
Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources. CoRR (2022)
Lorenzo Cerrone, Athul Vijayan, Tejasvinee Mody, Kay Schneitz, Fred A. Hamprecht
CellTypeGraph: A New Geometric Computer Vision Benchmark. CVPR (2022)
Enrique Fita Sanmartín, Sebastian Damrich, Fred A. Hamprecht
The Algebraic Path Problem for Graph Metrics. ICML (2022)
Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht
Directed Probabilistic Watershed. NeurIPS (2021)
Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht
Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice. ICCV (2021)
Sebastian Damrich, Fred A. Hamprecht
UMAP does not reproduce high-dimensional similarities due to negative sampling. CoRR (2021)
Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning. IEEE Trans. Pattern Anal. Mach. Intell. 43 (10) (2021)
Quentin Garrido, Sebastian Damrich, Alexander Jäger, Dario Cerletti, Manfred Claassen, Laurent Najman, Fred A. Hamprecht
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder. CoRR (2021)
Sebastian Damrich, Fred A. Hamprecht
On UMAP's True Loss Function. NeurIPS (2021)
Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht
Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice. CoRR (2021)
Florin C. Walter, Sebastian Damrich, Fred A. Hamprecht
Multistar: Instance Segmentation Of Overlapping Objects With Star-Convex Polygons. ISBI (2021)
Steffen Wolf, Fred A. Hamprecht, Jan Funke
Instance Separation Emerges from Inpainting. CoRR (2020)
Alberto Bailoni, Constantin Pape, Steffen Wolf, Anna Kreshuk, Fred A. Hamprecht
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks. CoRR (2020)
Alberto Bailoni, Constantin Pape, Steffen Wolf, Anna Kreshuk, Fred A. Hamprecht
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks. GCPR (2020)
Steffen Wolf, Yuyan Li, Constantin Pape, Alberto Bailoni, Anna Kreshuk, Fred A. Hamprecht
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation. ECCV (6) (2020)
Elke Kirschbaum, Alberto Bailoni, Fred A. Hamprecht
DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging. MICCAI (5) (2020)
Thomas M. Hehn, Julian F. P. Kooij, Fred A. Hamprecht
End-to-End Learning of Decision Trees and Forests. Int. J. Comput. Vis. 128 (4) (2020)
Steffen Wolf, Fred A. Hamprecht, Jan Funke
Inpainting Networks Learn to Separate Cells in Microscopy Images. BMVC (2020)
Florin C. Walter, Sebastian Damrich, Fred A. Hamprecht
MultiStar: Instance Segmentation of Overlapping Objects with Star-Convex Polygons. CoRR (2020)
Alberto Bailoni, Constantin Pape, Steffen Wolf, Thorsten Beier, Anna Kreshuk, Fred A. Hamprecht
A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation. CoRR (2019)
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. UAI (2019)
Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville
On the Spectral Bias of Neural Networks. ICML (2019)
Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht
Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning. NeurIPS (2019)
Elke Kirschbaum, Alberto Bailoni, Fred A. Hamprecht
DISCo for the CIA: Deep learning, Instance Segmentation, and Correlations for Calcium Imaging Analysis. CoRR (2019)
Lorenzo Cerrone, Alexander Zeilmann, Fred A. Hamprecht
End-to-End Learned Random Walker for Seeded Image Segmentation. CoRR (2019)
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir
Deep Active Learning with Adaptive Acquisition. IJCAI (2019)
Steffen Wolf, Yuyan Li, Constantin Pape, Alberto Bailoni, Anna Kreshuk, Fred A. Hamprecht
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation. CoRR (2019)
Lorenzo Cerrone, Alexander Zeilmann, Fred A. Hamprecht
End-To-End Learned Random Walker for Seeded Image Segmentation. CVPR (2019)
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir
Deep Active Learning with Adaptive Acquisition. CoRR (2019)
Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht
The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning. CoRR (2019)
Elke Kirschbaum, Manuel Haußmann, Steffen Wolf, Hannah Sonntag, Justus Schneider, Shehabeldin Elzoheiry, Oliver Kann, Daniel Durstewitz, Fred A. Hamprecht
LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos. ICLR (Poster) (2019)
Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht
Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning. CoRR (2019)
Felix Draxler, Kambis Veschgini, Manfred Salmhofer, Fred A. Hamprecht
Essentially No Barriers in Neural Network Energy Landscape. CoRR (2018)
Steffen Wolf, Constantin Pape, Alberto Bailoni, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht
The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV (4) (2018)
Maurice Weiler, Fred A. Hamprecht, Martin Storath
Learning Steerable Filters for Rotation Equivariant CNNs. CVPR (2018)
Nasim Rahaman, Devansh Arpit, Aristide Baratin, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville
On the Spectral Bias of Deep Neural Networks. CoRR (2018)
Thomas M. Hehn, Fred A. Hamprecht
End-to-End Learning of Deterministic Decision Trees. GCPR (2018)
Carsten Haubold, Virginie Uhlmann, Michael Unser, Fred A. Hamprecht
Diverse M-Best Solutions by Dynamic Programming. CoRR (2018)
Nikola Krasowski, Thorsten Beier, Graham Knott, Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk
Neuron Segmentation With High-Level Biological Priors. IEEE Trans. Medical Imaging 37 (4) (2018)
Virginie Uhlmann, Carsten Haubold, Fred A. Hamprecht, Michael Unser
DiversePathsJ: diverse shortest paths for bioimage analysis. Bioinform. 34 (3) (2018)
Melih Kandemir, Manuel Haußmann, Fred A. Hamprecht
Sampling-Free Variational Inference of Bayesian Neural Nets. CoRR (2018)
Felix Draxler, Kambis Veschgini, Manfred Salmhofer, Fred A. Hamprecht
Essentially No Barriers in Neural Network Energy Landscape. ICML (2018)
Sven Peter, Ferran Diego, Fred A. Hamprecht, Boaz Nadler
Cost efficient gradient boosting. NIPS (2017)
Sven Peter, Elke Kirschbaum, Martin Both, Lee Campbell, Brandon Harvey, Conor Heins, Daniel Durstewitz, Ferran Diego, Fred A. Hamprecht
Sparse convolutional coding for neuronal assembly detection. NIPS (2017)
Carsten Haubold, Virginie Uhlmann, Michael Unser, Fred A. Hamprecht
Diverse M-Best Solutions by Dynamic Programming. GCPR (2017)
Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht
Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV (2017)
Thomas Hehn, Fred A. Hamprecht
End-to-end Learning of Deterministic Decision Trees. CoRR (2017)
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir
Variational Bayesian Multiple Instance Learning with Gaussian Processes. CVPR (2017)
Maurice Weiler, Fred A. Hamprecht, Martin Storath
Learning Steerable Filters for Rotation Equivariant CNNs. CoRR (2017)
Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht
Learned Watershed: End-to-End Learning of Seeded Segmentation. CoRR (2017)
Matthias von Borstel, Melih Kandemir, Philip Schmidt, Madhavi K. Rao, Kumar T. Rajamani, Fred A. Hamprecht
Gaussian Process Density Counting from Weak Supervision. ECCV (1) (2016)
Ferran Diego, Fred A. Hamprecht
Structured Regression Gradient Boosting. CVPR (2016)
Melih Kandemir, Manuel Haußmann, Ferran Diego, Kumar T. Rajamani, Jeroen van der Laak, Fred A. Hamprecht
Variational Weakly Supervised Gaussian Processes. BMVC (2016)
Martin Schiegg, Ferran Diego, Fred A. Hamprecht
Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV (3) (2016)
Thorsten Beier, Björn Andres, Ullrich Köthe, Fred A. Hamprecht
An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV (2) (2016)
Carsten Haubold, Janez Ales, Steffen Wolf, Fred A. Hamprecht
A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets. ECCV (7) (2016)
Melih Kandemir, Christian Wojek, Fred A. Hamprecht
Cell Event Detection in Phase-Contrast Microscopy Sequences from Few Annotations. MICCAI (3) (2015)
Anna Kreshuk, Jan Funke, Albert Cardona, Fred A. Hamprecht
Who Is Talking to Whom: Synaptic Partner Detection in Anisotropic Volumes of Insect Brain. MICCAI (1) (2015)
Melih Kandemir, Fred A. Hamprecht
Computer-aided diagnosis from weak supervision: A benchmarking study. Comput. Medical Imaging Graph. 42 (2015)
Nikola Krasowski, Thorsten Beier, Graham W. Knott, Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk
Improving 3D EM data segmentation by joint optimization over boundary evidence and biological priors. ISBI (2015)
Martin Schiegg, Ben Heuer, Carsten Haubold, Steffen Wolf, Ullrich Köthe, Fred A. Hamprecht
Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models. ISBI (2015)
Thorsten Beier, Fred A. Hamprecht, Jörg H. Kappes
Fusion moves for correlation clustering. CVPR (2015)
Jan Funke, Fred A. Hamprecht, Chong Zhang
Learning to Segment: Training Hierarchical Segmentation under a Topological Loss. MICCAI (3) (2015)
Martin Schiegg, Philipp Hanslovsky, Carsten Haubold, Ullrich Köthe, Lars Hufnagel, Fred A. Hamprecht
Graphical model for joint segmentation and tracking of multiple dividing cells. Bioinform. 31 (6) (2015)
Melih Kandemir, Fred A. Hamprecht
The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors. FE@NIPS (2015)
Jörg H. Kappes, Björn Andres, Fred A. Hamprecht, Christoph Schnörr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Thorben Kröger, Jan Lellmann, Nikos Komodakis, Bogdan Savchynskyy, Carsten Rother
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int. J. Comput. Vis. 115 (2) (2015)
Thorben Kröger, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht
Asymmetric Cuts: Joint Image Labeling and Partitioning. GCPR (2014)
Julian Yarkony, Thorsten Beier, Pierre Baldi, Fred A. Hamprecht
Parallel Multicut Segmentation via Dual Decomposition. NFMCP (2014)
F. Boray Tek, Thorben Kröger, Shawn Mikula, Fred A. Hamprecht
Automated cell nucleus detection for large-volume electron microscopy of neural tissue. ISBI (2014)
Melih Kandemir, Annette Feuchtinger, Axel Walch, Fred A. Hamprecht
Digital pathology: Multiple instance learning can detect Barrett's cancer. ISBI (2014)
Xinghua Lou, Martin Schiegg, Fred A. Hamprecht
Active Structured Learning for Cell Tracking: Algorithm, Framework, and Usability. IEEE Trans. Medical Imaging 33 (4) (2014)
Melih Kandemir, Fred A. Hamprecht
Instance Label Prediction by Dirichlet Process Multiple Instance Learning. UAI (2014)
Chong Zhang, Florian Huber, Michael Knop, Fred A. Hamprecht
Yeast cell detection and segmentation in bright field microscopy. ISBI (2014)
Melih Kandemir, José C. Rubio, Ute Schmidt, Christian Wojek, Johannes Welbl, Björn Ommer, Fred A. Hamprecht
Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. MICCAI (2) (2014)
Melih Kandemir, Chong Zhang, Fred A. Hamprecht
Empowering Multiple Instance Histopathology Cancer Diagnosis by Cell Graphs. MICCAI (2) (2014)
Christoph N. Straehle, Melih Kandemir, Ullrich Köthe, Fred A. Hamprecht
Multiple Instance Learning with Response-Optimized Random Forests. ICPR (2014)
Luca Fiaschi, Ferran Diego Andilla, Konstantin Gregor, Martin Schiegg, Ullrich Köthe, Marta Zlatic, Fred A. Hamprecht
Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning. CVPR (2014)
Thorsten Beier, Thorben Kröger, Jörg H. Kappes, Ullrich Köthe, Fred A. Hamprecht
Cut, Glue, & Cut: A Fast, Approximate Solver for Multicut Partitioning. CVPR (2014)
Amnon Drory, Carsten Haubold, Shai Avidan, Fred A. Hamprecht
Semi-Global Matching: A Principled Derivation in Terms of Message Passing. GCPR (2014)
Jörg H. Kappes, Björn Andres, Fred A. Hamprecht, Christoph Schnörr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Thorben Kröger, Jan Lellmann, Nikos Komodakis, Bogdan Savchynskyy, Carsten Rother
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR (2014)
Chong Zhang, Julian Yarkony, Fred A. Hamprecht
Cell Detection and Segmentation Using Correlation Clustering. MICCAI (1) (2014)
Ferran Diego Andilla, Fred A. Hamprecht
Sparse Space-Time Deconvolution for Calcium Image Analysis. NIPS (2014)
Ferran Diego Andilla, Fred A. Hamprecht
Learning Multi-level Sparse Representations. NIPS (2013)
Martin Schiegg, Philipp Hanslovsky, Bernhard X. Kausler, Lars Hufnagel, Fred A. Hamprecht
Conservation Tracking. ICCV (2013)
Thorben Kröger, Shawn Mikula, Winfried Denk, Ullrich Köthe, Fred A. Hamprecht
Learning to Segment Neurons with Non-local Quality Measures. MICCAI (2) (2013)
Luca Fiaschi, Gregor Konstantin, Bruno Afonso, Marta Zlatic, Fred A. Hamprecht
Keeping count: Leveraging temporal context to count heavily overlapping objects. ISBI (2013)
Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht
Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria. ICCV (2013)
Christoph N. Straehle, Sven Peter, Ullrich Köthe, Fred A. Hamprecht
K-Smallest Spanning Tree Segmentations. GCPR (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Fred A. Hamprecht