Hamprecht, Fred A.

45 publications

ICLR 2025 Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing Peter Lippmann, Gerrit Gerhartz, Roman Remme, Fred A. Hamprecht

NeurIPS 2025 Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant Jonas Spinner, Luigi Favaro, Peter Lippmann, Sebastian Pitz, Gerrit Gerhartz, Tilman Plehn, Fred A. Hamprecht

NeurIPS 2024 Truth Is Universal: Robust Detection of Lies in LLMs Lennart Bürger, Fred A. Hamprecht, Boaz Nadler

ICLR 2023 From $t$-SNE to UMAP with Contrastive Learning Sebastian Damrich, Niklas Böhm, Fred A Hamprecht, Dmitry Kobak

ICML 2023 Geometric Autoencoders - What You See Is What You Decode Philipp Nazari, Sebastian Damrich, Fred A Hamprecht

CVPR 2022 CellTypeGraph: A New Geometric Computer Vision Benchmark Lorenzo Cerrone, Athul Vijayan, Tejasvinee Mody, Kay Schneitz, Fred A. Hamprecht

CVPR 2022 GASP, a Generalized Framework for Agglomerative Clustering of Signed Graphs and Its Application to Instance Segmentation Alberto Bailoni, Constantin Pape, Nathan Hütsch, Steffen Wolf, Thorsten Beier, Anna Kreshuk, Fred A. Hamprecht

NeurIPS 2022 Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht

NeurIPS 2021 Directed Probabilistic Watershed Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht

ICCV 2021 Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht

NeurIPS 2021 On UMAP's True Loss Function Sebastian Damrich, Fred A. Hamprecht

ECCV 2020 Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed Steffen Wolf, Yuyan Li, Constantin Pape, Alberto Bailoni, Anna Kreshuk, Fred A. Hamprecht

IJCAI 2019 Deep Active Learning with Adaptive Acquisition Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir

ICLR 2019 LeMoNADe: Learned Motif and Neuronal Assembly Detection in Calcium Imaging Videos Elke Kirschbaum, Manuel Haußmann, Steffen Wolf, Hannah Sonntag, Justus Schneider, Shehabeldin Elzoheiry, Oliver Kann, Daniel Durstewitz, Fred A Hamprecht

NeurIPS 2019 Probabilistic Watershed: Sampling All Spanning Forests for Seeded Segmentation and Semi-Supervised Learning Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht

UAI 2019 Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir

NeurIPS 2017 Cost Efficient Gradient Boosting Sven Peter, Ferran Diego, Fred A. Hamprecht, Boaz Nadler

NeurIPS 2017 Sparse Convolutional Coding for Neuronal Assembly Detection Sven Peter, Elke Kirschbaum, Martin Both, Lee Campbell, Brandon Harvey, Conor Heins, Daniel Durstewitz, Ferran Diego, Fred A. Hamprecht

CVPR 2017 Variational Bayesian Multiple Instance Learning with Gaussian Processes Manuel Haussmann, Fred A. Hamprecht, Melih Kandemir

ECCV 2016 A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets Carsten Haubold, Janez Ales, Steffen Wolf, Fred A. Hamprecht

ECCV 2016 An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem Thorsten Beier, Björn Andres, Ullrich Köthe, Fred A. Hamprecht

ECCV 2016 Gaussian Process Density Counting from Weak Supervision Matthias von Borstel, Melih Kandemir, Philip Schmidt, Madhavi K. Rao, Kumar T. Rajamani, Fred A. Hamprecht

ECCV 2016 Learning Diverse Models: The Coulomb Structured Support Vector Machine Martin Schiegg, Ferran Diego, Fred A. Hamprecht

CVPR 2016 Structured Regression Gradient Boosting Ferran Diego, Fred A. Hamprecht

CVPR 2015 Fusion Moves for Correlation Clustering Thorsten Beier, Fred A. Hamprecht, Jorg H. Kappes

CVPR 2014 Cut, GLUE & Cut: A Fast, Approximate Solver for Multicut Partitioning Thorsten Beier, Thorben Kroeger, Jorg H. Kappes, Ullrich Kothe, Fred A. Hamprecht

UAI 2014 Instance Label Prediction by Dirichlet Process Multiple Instance Learning Melih Kandemir, Fred A. Hamprecht

NeurIPS 2014 Sparse Space-Time Deconvolution for Calcium Image Analysis Ferran Diego Andilla, Fred A. Hamprecht

CVPR 2014 Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning Luca Fiaschi, Ferran Diego, Konstantin Gregor, Martin Schiegg, Ullrich Koethe, Marta Zlatic, Fred A. Hamprecht

ICCV 2013 Conservation Tracking Martin Schiegg, Philipp Hanslovsky, Bernhard X. Kausler, Lars Hufnagel, Fred A. Hamprecht

NeurIPS 2013 Learning Multi-Level Sparse Representations Ferran Diego Andilla, Fred A. Hamprecht

ICCV 2013 Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria Christoph Straehle, Ullrich Koethe, Fred A. Hamprecht

ECCV 2012 A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness Bernhard X. Kausler, Martin Schiegg, Björn Andres, Martin S. Lindner, Ullrich Köthe, Heike Leitte, Jochen Wittbrodt, Lars Hufnagel, Fred A. Hamprecht

UAI 2012 Active Learning with Distributional Estimates Jens Röder, Boaz Nadler, Kevin Kunzmann, Fred A. Hamprecht

CVPR 2012 Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data Jan Funke, Björn Andres, Fred A. Hamprecht, Albert Cardona, Matthew Cook

ECCV 2012 Globally Optimal Closed-Surface Segmentation for Connectomics Björn Andres, Thorben Kröger, Kevin L. Briggman, Winfried Denk, Natalya Korogod, Graham Knott, Ullrich Köthe, Fred A. Hamprecht

CVPR 2012 Learning to Segment Dense Cell Nuclei with Shape Prior Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt, Fred A. Hamprecht

CVPR 2012 Seeded Watershed Cut Uncertainty Estimators for Guided Interactive Segmentation Christoph N. Straehle, Ullrich Köthe, Graham Knott, Kevin L. Briggman, Winfried Denk, Fred A. Hamprecht

ICML 2012 Structured Learning from Partial Annotations Xinghua Lou, Fred A. Hamprecht

ECCV 2012 The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models Björn Andres, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht

ECML-PKDD 2011 On Oblique Random Forests Bjoern H. Menze, B. Michael Kelm, Daniel Nicolas Splitthoff, Ullrich Köthe, Fred A. Hamprecht

ICCV 2011 Probabilistic Image Segmentation with Closedness Constraints Björn Andres, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht

NeurIPS 2011 Structured Learning for Cell Tracking Xinghua Lou, Fred A. Hamprecht

CVPR 2008 On Errors-in-Variables Regression with Arbitrary Covariance and Its Application to Optical Flow Estimation Björn Andres, Claudia Kondermann, Daniel Kondermann, Ullrich Köthe, Fred A. Hamprecht, Christoph S. Garbe

CVPRW 2006 Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM B. Michael Kelm, Natalie Mueller, Bjoern H. Menze, Fred A. Hamprecht