Fred A. Hamprecht
49 publications
10 venues
H Index 22
Affiliation
University of Heidelberg, Interdisciplinary Center for Scientific Computing, GermanyLinks
| Name | Venue | Year | citations |
|---|---|---|---|
Geometric Autoencoders - What You See is What You Decode.
|
ICML | 2023 | 0 |
| From $t$-SNE to UMAP with contrastive learning.
|
ICLR | 2023 | 0 |
| CellTypeGraph: A New Geometric Computer Vision Benchmark.
|
CVPR | 2022 | 0 |
| The Algebraic Path Problem for Graph Metrics.
|
ICML | 2022 | 0 |
| GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation.
|
CVPR | 2022 | 0 |
| Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources.
|
NIPS/NeurIPS | 2022 | 0 |
| On UMAP's True Loss Function.
|
NIPS/NeurIPS | 2021 | 10 |
| Directed Probabilistic Watershed.
|
NIPS/NeurIPS | 2021 | 0 |
| Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice.
|
ICCV | 2021 | 0 |
| The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning.
|
TPAMI | 2021 | 0 |
| The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation.
|
ECCV | 2020 | 0 |
| Deep Active Learning with Adaptive Acquisition.
|
IJCAI | 2019 | 21 |
| Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning.
|
NIPS/NeurIPS | 2019 | 3 |
| End-To-End Learned Random Walker for Seeded Image Segmentation.
|
CVPR | 2019 | 13 |
| On the Spectral Bias of Neural Networks.
|
ICML | 2019 | 0 |
| Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation.
|
UAI | 2019 | 0 |
| Essentially No Barriers in Neural Network Energy Landscape.
|
ICML | 2018 | 255 |
| The Mutex Watershed: Efficient, Parameter-Free Image Partitioning.
|
ECCV | 2018 | 41 |
| Learning Steerable Filters for Rotation Equivariant CNNs.
|
CVPR | 2018 | 0 |
| Cost efficient gradient boosting.
|
NIPS/NeurIPS | 2017 | 30 |
| Variational Bayesian Multiple Instance Learning with Gaussian Processes.
|
CVPR | 2017 | 22 |
| Learned Watershed: End-to-End Learning of Seeded Segmentation.
|
ICCV | 2017 | 29 |
| Sparse convolutional coding for neuronal assembly detection.
|
NIPS/NeurIPS | 2017 | 11 |
| Structured Regression Gradient Boosting.
|
CVPR | 2016 | 4 |
| Gaussian Process Density Counting from Weak Supervision.
|
ECCV | 2016 | 30 |
| Learning Diverse Models: The Coulomb Structured Support Vector Machine.
|
ECCV | 2016 | 3 |
| An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem.
|
ECCV | 2016 | 39 |
| A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets.
|
ECCV | 2016 | 12 |
| Fusion moves for correlation clustering.
|
CVPR | 2015 | 40 |
| Instance Label Prediction by Dirichlet Process Multiple Instance Learning.
|
UAI | 2014 | 14 |
| Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning.
|
CVPR | 2014 | 23 |
| Sparse Space-Time Deconvolution for Calcium Image Analysis.
|
NIPS/NeurIPS | 2014 | 61 |
| Cut, Glue, & Cut: A Fast, Approximate Solver for Multicut Partitioning.
|
CVPR | 2014 | 0 |
| Conservation Tracking.
|
ICCV | 2013 | 63 |
| Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria.
|
ICCV | 2013 | 5 |
| Learning Multi-level Sparse Representations.
|
NIPS/NeurIPS | 2013 | 26 |
| A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems.
|
CVPR | 2013 | 218 |
| Learning to segment dense cell nuclei with shape prior.
|
CVPR | 2012 | 59 |
| Seeded watershed cut uncertainty estimators for guided interactive segmentation.
|
CVPR | 2012 | 27 |
| Efficient automatic 3D-reconstruction of branching neurons from EM data.
|
CVPR | 2012 | 78 |
| Globally Optimal Closed-Surface Segmentation for Connectomics.
|
ECCV | 2012 | 95 |
| A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness.
|
ECCV | 2012 | 44 |
| Active Learning with Distributional Estimates.
|
UAI | 2012 | 5 |
| The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models.
|
ECCV | 2012 | 30 |
| Structured Learning from Partial Annotations.
|
ICML | 2012 | 37 |
| On Oblique Random Forests.
|
ECML/PKDD | 2011 | 223 |
| Probabilistic image segmentation with closedness constraints.
|
ICCV | 2011 | 99 |
| Structured Learning for Cell Tracking.
|
NIPS/NeurIPS | 2011 | 41 |
| On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation.
|
CVPR | 2008 | 2 |