Fred A. Hamprecht
26 papers · 2011–2025 · 7 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (7) 🏃 Academic Marathon (14) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (7)
🌍
Conference Polyglot
(7)
🏃
Academic Marathon
(14)
🧭
Keyword Pioneer
🌟
Keyword Trendsetter Combo
(3)
🏆
Keyword Champion
(2)
🔥
Unstoppable
(10)
📈
Trend Setter
💎
Century Club
(26)
🚀
Conference Pioneer
🗃️
Keyword Collector
(119)
Conferences
NIPS (10)
CVPR (9)
ICCV (3)
ECCV (1)
ICLR (1)
MICCAI (1)
UAI (1)
Top co-authors
Keywords
image segmentation
(4)
random walker
(3)
weakly supervised learning
(3)
semi-supervised learning
(3)
seeded segmentation
(3)
sparse representation
(2)
spike timing
(2)
calcium imaging
(2)
cell tracking
(2)
structured learning
(2)
gradient boosting
(2)
combinatorial optimization
(2)
object tracking
(2)
spanning forest
(2)
graph partitioning
(2)
convolutional neural network
(2)
variational inference
(2)
optimal transport
(1)
budget-aware learning
(1)
graph theory
(1)
Papers
Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
ICLR 2025
Truth is Universal: Robust Detection of Lies in LLMs
NIPS 2024
SynCellFactory: Generative Data Augmentation for Cell Tracking
MICCAI 2024
GASP, a Generalized Framework for Agglomerative Clustering of Signed Graphs and Its Application to Instance Segmentation
CVPR 2022
Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
NIPS 2022
CellTypeGraph: A New Geometric Computer Vision Benchmark
CVPR 2022
On UMAP's True Loss Function
NIPS 2021
Directed Probabilistic Watershed
NIPS 2021
Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice
ICCV 2021
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed
ECCV 2020
End-To-End Learned Random Walker for Seeded Image Segmentation
CVPR 2019
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
UAI 2019
Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning
NIPS 2019
Learning Steerable Filters for Rotation Equivariant CNNs
CVPR 2018
Variational Bayesian Multiple Instance Learning With Gaussian Processes
CVPR 2017
Sparse convolutional coding for neuronal assembly detection
NIPS 2017
Cost efficient gradient boosting
NIPS 2017
Structured Regression Gradient Boosting
CVPR 2016
Fusion Moves for Correlation Clustering
CVPR 2015
Tracking Indistinguishable Translucent Objects over Time using Weakly Supervised Structured Learning
CVPR 2014
Cut, Glue & Cut: A Fast, Approximate Solver for Multicut Partitioning
CVPR 2014
Sparse Space-Time Deconvolution for Calcium Image Analysis
NIPS 2014
Learning Multi-level Sparse Representations
NIPS 2013
Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria
ICCV 2013
Conservation Tracking
ICCV 2013
Structured Learning for Cell Tracking
NIPS 2011