Joachim M. Buhmann
87 publications
15 venues
H Index 39
Affiliation
ETH Zurich, SwitzerlandUniversity of Bonn, Germany
Links
| Name | Venue | Year | citations |
|---|---|---|---|
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective.
|
NIPS/NeurIPS | 2023 | 0 |
| Explore In-Context Learning for 3D Point Cloud Understanding.
|
NIPS/NeurIPS | 2023 | 0 |
| Learning Long-Term Crop Management Strategies with CyclesGym.
|
NIPS/NeurIPS | 2022 | 0 |
| Statistical and computational thresholds for the planted k-densest sub-hypergraph problem.
|
AISTATS | 2022 | 0 |
| Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.
|
NIPS/NeurIPS | 2022 | 0 |
| Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling.
|
ICLR | 2021 | 9 |
| From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models.
|
ICML | 2020 | 4 |
| Learning Counterfactual Representations for Estimating Individual Dose-Response Curves.
|
AAAI | 2020 | 0 |
| Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference.
|
ICML | 2019 | 19 |
| Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs.
|
AISTATS | 2019 | 0 |
| Scalable Variational Inference for Dynamical Systems.
|
NIPS/NeurIPS | 2017 | 40 |
| Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms.
|
NIPS/NeurIPS | 2017 | 15 |
| Efficient and Flexible Inference for Stochastic Systems.
|
NIPS/NeurIPS | 2017 | 6 |
| Guarantees for Greedy Maximization of Non-submodular Functions with Applications.
|
ICML | 2017 | 198 |
| Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains.
|
AISTATS | 2017 | 0 |
| Scalable Adaptive Stochastic Optimization Using Random Projections.
|
NIPS/NeurIPS | 2016 | 19 |
| TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks.
|
CVPR | 2016 | 212 |
| Transformation-Invariant Convolutional Jungles.
|
CVPR | 2015 | 21 |
| Asymptotic analysis of estimators on multi-label data.
|
MLJ | 2015 | 1 |
| Kickback Cuts Backprop's Red-Tape: Biologically Plausible Credit Assignment in Neural Networks.
|
AAAI | 2015 | 0 |
| Fast and Robust Least Squares Estimation in Corrupted Linear Models.
|
NIPS/NeurIPS | 2014 | 43 |
| Correlated random features for fast semi-supervised learning.
|
NIPS/NeurIPS | 2013 | 45 |
| Ellipsoidal Multiple Instance Learning.
|
ICML | 2013 | 20 |
| Weakly supervised structured output learning for semantic segmentation.
|
CVPR | 2012 | 174 |
| Bayesian mixed-effects inference on classification performance in hierarchical data sets.
|
JMLR | 2012 | 26 |
| Active learning for semantic segmentation with expected change.
|
CVPR | 2012 | 126 |
| Information Theoretic Model Validation for Spectral Clustering.
|
AISTATS | 2012 | 29 |
| Multi-Assignment Clustering for Boolean Data.
|
JMLR | 2012 | 0 |
| The Minimum Transfer Cost Principle for Model-Order Selection.
|
ECML/PKDD | 2011 | 18 |
| Weakly supervised semantic segmentation with a multi-image model.
|
ICCV | 2011 | 175 |
| Learning the Compositional Nature of Visual Object Categories for Recognition.
|
TPAMI | 2010 | 83 |
| Entropy and Margin Maximization for Structured Output Learning.
|
ECML/PKDD | 2010 | 42 |
| Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning.
|
CVPR | 2010 | 159 |
| Neuron geometry extraction by perceptual grouping in ssTEM images.
|
CVPR | 2010 | 108 |
| Multi-assignment clustering for Boolean data.
|
ICML | 2009 | 140 |
| Structure Identification by Optimized Interventions.
|
AISTATS | 2009 | 10 |
| Spanning Tree Approximations for Conditional Random Fields.
|
AISTATS | 2009 | 21 |
| Optimized expected information gain for nonlinear dynamical systems.
|
ICML | 2009 | 22 |
| Classification of Multi-labeled Data: A Generative Approach.
|
ECML/PKDD | 2008 | 33 |
| Probabilistic image registration and anomaly detection by nonlinear warping.
|
CVPR | 2008 | 15 |
| On Relevant Dimensions in Kernel Feature Spaces.
|
JMLR | 2008 | 131 |
| Expectation-maximization for sparse and non-negative PCA.
|
ICML | 2008 | 118 |
| Cluster analysis of heterogeneous rank data.
|
ICML | 2007 | 114 |
| Kernel-Based Grouping of Histogram Data.
|
ECML/PKDD | 2007 | 0 |
| Robust Image Segmentation Using Resampling and Shape Constraints.
|
TPAMI | 2007 | 26 |
| Learning the Compositional Nature of Visual Objects.
|
CVPR | 2007 | 60 |
| PerformancePrediction Challenge.
|
IJCNN | 2006 | 17 |
| Model Order Selection and Cue Combination for Image Segmentation.
|
CVPR | 2006 | 56 |
| Smooth Image Segmentation by Nonparametric Bayesian Inference.
|
ECCV | 2006 | 36 |
| Learning Compositional Categorization Models.
|
ECCV | 2006 | 47 |
| Denoising and Dimension Reduction in Feature Space.
|
NIPS/NeurIPS | 2006 | 16 |
| Learning with Constrained and Unlabelled Data.
|
CVPR | 2005 | 100 |
| Combining partitions by probabilistic label aggregation.
|
KDD | 2005 | 32 |
| Fusion of Similarity Data in Clustering.
|
NIPS/NeurIPS | 2005 | 41 |
| A Hidden Markov Model for de Novo Peptide Sequencing.
|
NIPS/NeurIPS | 2004 | 178 |
| Shape Constrained Image Segmentation by Parametric Distributional Clustering.
|
CVPR | 2004 | 4 |
| Bagging for Path-Based Clustering.
|
TPAMI | 2003 | 222 |
| Path-Based Clustering for Grouping of Smooth Curves and Texture Segmentation.
|
TPAMI | 2003 | 231 |
| Clustering with the Connectivity Kernel.
|
NIPS/NeurIPS | 2003 | 91 |
| Optimal Cluster Preserving Embedding of Nonmetric Proximity Data.
|
TPAMI | 2003 | 212 |
| Going Metric: Denoising Pairwise Data.
|
NIPS/NeurIPS | 2002 | 75 |
| Stability-Based Model Selection.
|
NIPS/NeurIPS | 2002 | 111 |
| Parametric Distributional Clustering for Image Segmentation.
|
ECCV | 2002 | 37 |
| Stability-Based Model Order Selection in Clustering with Applications to Gene Expression Data.
|
ICANN | 2002 | 18 |
| Coupled Clustering: A Method for Detecting Structural Correspondence.
|
JMLR | 2002 | 0 |
| Coupled Clustering: a Method for Detecting Structural Correspondence.
|
ICML | 2001 | 39 |
| Contextual Classification by Entropy-Based Polygonization.
|
CVPR | 2001 | 5 |
| Topology Free Hidden Markov Models: Application to Background Modeling.
|
ICCV | 2001 | 244 |
| The Noisy Euclidean Traveling Salesman Problem and Learning.
|
NIPS/NeurIPS | 2001 | 12 |
| Empirical Evaluation of Dissimilarity Measures for Color and Texture.
|
ICCV | 1999 | 744 |
| Histogram Clustering for Unsupervised Image Segmentation.
|
CVPR | 1999 | 94 |
| Model Selection in Clustering by Uniform Convergence Bounds.
|
NIPS/NeurIPS | 1999 | 8 |
| Visualizing Group Structure.
|
NIPS/NeurIPS | 1998 | 1 |
| Unsupervised Texture Segmentation in a Deterministic Annealing Framework.
|
TPAMI | 1998 | 246 |
| On Spatial Quantization of Color Images.
|
ECCV | 1998 | 79 |
| Multiscale Annealing for Real-Time Unsupervised Texture Segmentation.
|
ICCV | 1998 | 0 |
| Pairwise Data Clustering by Deterministic Annealing.
|
TPAMI | 1997 | 541 |
| Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval.
|
CVPR | 1997 | 304 |
| Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis.
|
NIPS/NeurIPS | 1997 | 8 |
| Correction to "Pairwise Data Clustering by Deterministic Annealing".
|
TPAMI | 1997 | 7 |
| Active Data Clustering.
|
NIPS/NeurIPS | 1997 | 70 |
| Inferring Hierarchical Clustering Structures by Deterministic Annealing.
|
KDD | 1996 | 8 |
| An Annealed "Neural Gas" Network for Robust Vector Quantization.
|
ICANN | 1996 | 10 |
| Multidimensional Scaling and Data Clustering.
|
NIPS/NeurIPS | 1994 | 49 |
| Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina.
|
NIPS/NeurIPS | 1993 | 22 |
| Central and Pairwise Data Clustering by Competitive Neural Networks.
|
NIPS/NeurIPS | 1993 | 10 |
| Size and distortion invariant object recognition by hierarchical graph matching.
|
IJCNN | 1990 | 100 |