Matthias A. Hein
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Matthias A. Heincomputer-science Degrees
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Artificial Intelligence
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Computer Science
Matthias A. Hein's Degrees
- PhD Computer Science University of Tübingen
- Masters Computer Science University of Tübingen
- Bachelors Computer Science University of Tübingen
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Why Is Matthias A. Hein Influential?
(Suggest an Edit or Addition)Matthias A. Hein's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks (2020) (805)
- Latent Embeddings for Zero-Shot Classification (2016) (610)
- Simple Does It: Weakly Supervised Instance and Semantic Segmentation (2016) (583)
- Square Attack: a query-efficient black-box adversarial attack via random search (2019) (461)
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation (2017) (422)
- Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem (2018) (361)
- From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians (2005) (341)
- Spectral clustering based on the graph p-Laplacian (2009) (312)
- The Loss Surface of Deep and Wide Neural Networks (2017) (267)
- Graph Laplacians and their Convergence on Random Neighborhood Graphs (2006) (260)
- An integer linear programming approach for finding deregulated subgraphs in regulatory networks (2011) (259)
- RobustBench: a standardized adversarial robustness benchmark (2020) (250)
- Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack (2019) (236)
- An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA (2010) (208)
- Hilbertian Metrics and Positive Definite Kernels on Probability Measures (2005) (203)
- Variants of RMSProp and Adagrad with Logarithmic Regret Bounds (2017) (202)
- Intrinsic dimensionality estimation of submanifolds in Rd (2005) (199)
- Disentangling Adversarial Robustness and Generalization (2018) (198)
- Manifold Denoising (2006) (194)
- Influence of graph construction on graph-based clustering measures (2008) (171)
- Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization (2012) (168)
- Provable Robustness of ReLU networks via Maximization of Linear Regions (2018) (148)
- Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks (2020) (146)
- Measure Based Regularization (2003) (136)
- Sparse and Imperceivable Adversarial Attacks (2019) (127)
- The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited (2013) (126)
- Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters (2009) (126)
- Error Estimates for Spectral Convergence of the Graph Laplacian on Random Geometric Graphs Toward the Laplace–Beltrami Operator (2018) (124)
- Learning using privileged information: SV M+ and weighted SVM (2013) (121)
- Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction (2009) (105)
- Hitting and commute times in large random neighborhood graphs (2014) (102)
- Towards neural networks that provably know when they don't know (2019) (96)
- Optimization Landscape and Expressivity of Deep CNNs (2017) (95)
- Enhancement of Bright Video Features for HDR Displays (2008) (92)
- Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts (2011) (92)
- Estimation of positive definite M-matrices and structure learning for attractive Gaussian Markov Random fields (2014) (90)
- Towards realistic team formation in social networks based on densest subgraphs (2013) (89)
- Constrained 1-Spectral Clustering (2012) (86)
- Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel Classification (2016) (82)
- Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks (2019) (80)
- Loss Functions for Top-k Error: Analysis and Insights (2015) (75)
- Top-k Multiclass SVM (2015) (74)
- Uniform Convergence of Adaptive Graph-Based Regularization (2006) (74)
- On the loss landscape of a class of deep neural networks with no bad local valleys (2018) (73)
- Intrinsic Dimensionality Estimation of Submanifolds in R (2005) (72)
- Kernels, Associated Structures and Generalizations (2004) (72)
- Getting lost in space: Large sample analysis of the resistance distance (2010) (71)
- Logit Pairing Methods Can Fool Gradient-Based Attacks (2018) (67)
- A flexible tensor block coordinate ascent scheme for hypergraph matching (2015) (66)
- MeDeCom: discovery and quantification of latent components of heterogeneous methylomes (2017) (65)
- Classifier based graph construction for video segmentation (2015) (65)
- Sparse recovery by thresholded non-negative least squares (2011) (62)
- Maximal margin classification for metric spaces (2005) (61)
- Getting lost in space: large sample analysis of the commute distance (2010) (61)
- Adversarial Robustness on In- and Out-Distribution Improves Explainability (2020) (60)
- Non-parametric Regression Between Manifolds (2008) (59)
- Scalable Multitask Representation Learning for Scene Classification (2014) (55)
- How the result of graph clustering methods depends on the construction of the graph (2011) (48)
- Intrinsic Dimensionality Estimation of Submanifolds in Euclidean space (2005) (47)
- Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks (2019) (47)
- Nonparametric Regression between General Riemannian Manifolds (2010) (46)
- Cluster Identification in Nearest-Neighbor Graphs (2007) (45)
- Hitting and commute times in large graphs are often misleading (2010) (45)
- Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions (2018) (45)
- Provable robustness against all adversarial lp-perturbations for p≥1 (2019) (44)
- Weakly Supervised Object Boundaries (2015) (43)
- Certifiably Adversarially Robust Detection of Out-of-Distribution Data (2020) (39)
- Matrix factorization with binary components (2013) (38)
- Clustering Signed Networks with the Geometric Mean of Laplacians (2016) (36)
- Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks (2020) (35)
- A nodal domain theorem and a higher-order Cheeger inequality for the graph $p$-Laplacian (2016) (34)
- A unifying Perron-Frobenius theorem for nonnegative tensors via multi-homogeneous maps (2018) (34)
- Efficient Output Kernel Learning for Multiple Tasks (2015) (31)
- Relating Adversarially Robust Generalization to Flat Minima (2021) (31)
- The Perron-Frobenius Theorem for Multihomogeneous Mappings (2017) (30)
- Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods (2016) (30)
- The loss surface and expressivity of deep convolutional neural networks (2017) (28)
- An Efficient Multilinear Optimization Framework for Hypergraph Matching (2015) (26)
- Learning Must-Link Constraints for Video Segmentation Based on Spectral Clustering (2014) (25)
- Spectral Clustering of Signed Graphs via Matrix Power Means (2019) (25)
- The Power Mean Laplacian for Multilayer Graph Clustering (2018) (24)
- Geometrical aspects of statistical learning theory (2005) (24)
- Hilbertian Metrics on Probability Measures and Their Application in SVM?s (2004) (24)
- Bit Error Robustness for Energy-Efficient DNN Accelerators (2020) (24)
- Evaluating the Adversarial Robustness of Adaptive Test-time Defenses (2022) (23)
- Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks (2019) (22)
- Robust Nonparametric Regression with Metric-Space Valued Output (2009) (22)
- Robust PCA: Optimization of the Robust Reconstruction Error Over the Stiefel Manifold (2014) (21)
- Provably Robust Detection of Out-of-distribution Data (almost) for free (2021) (20)
- Isotope pattern deconvolution for peptide mass spectrometry by non-negative least squares/least absolute deviation template matching (2012) (20)
- Numerical evolution of axisymmetric, isolated systems in general relativity (2002) (20)
- Mind the box: l1-APGD for sparse adversarial attacks on image classifiers (2021) (20)
- Constrained fractional set programs and their application in local clustering and community detection (2013) (20)
- Community detection in networks via nonlinear modularity eigenvectors (2017) (19)
- A randomized gradient-free attack on ReLU networks (2018) (19)
- Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$ (2019) (18)
- Tight Continuous Relaxation of the Balanced k-Cut Problem (2014) (17)
- Tensor norm and maximal singular vectors of non-negative tensors - a Perron-Frobenius theorem, a Collatz-Wielandt characterization and a generalized power method (2015) (16)
- Manifold Denoising as Preprocessing for Finding Natural Representations of Data (2007) (16)
- Weakly Supervised Semantic Labelling and Instance Segmentation (2016) (16)
- Improved Image Boundaries for Better Video Segmentation (2016) (16)
- Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs (2019) (13)
- Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices (2015) (13)
- Manifold‐valued Thin‐Plate Splines with Applications in Computer Graphics (2008) (12)
- Nonlinear Eigenproblems in Data Analysis - Balanced Graph Cuts and the RatioDCA-Prox (2013) (11)
- Correction of noisy labels via mutual consistency check (2015) (11)
- Learnable Uncertainty under Laplace Approximations (2020) (10)
- Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities (2022) (9)
- Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data (2020) (8)
- Hitting times, commute distances and the spectral gap for large random geometric graphs (2010) (8)
- The Perron-Frobenius theorem for multi-homogeneous maps (2017) (7)
- Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators (2021) (6)
- Sparse Visual Counterfactual Explanations in Image Space (2022) (6)
- Adversarial robustness against multiple lp-threat models at the price of one and how to quickly fine-tune robust models to another threat model (2021) (6)
- Computing the norm of nonnegative matrices and the log-Sobolev constant of Markov chains (2020) (6)
- An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence (2020) (6)
- Being a Bit Frequentist Improves Bayesian Neural Networks (2021) (5)
- Adversarial Robustness against Multiple and Single lp-Threat Models via Quick Fine-Tuning of Robust Classifiers (2021) (5)
- Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks (2021) (5)
- Out-distribution aware Self-training in an Open World Setting (2020) (4)
- Diffusion Visual Counterfactual Explanations (2022) (4)
- Robust Principal Component Analysis as a Nonlinear Eigenproblem (2013) (4)
- Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation (2022) (4)
- Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations (2022) (3)
- Confidence-Calibrated Adversarial Training: Towards Robust Models Generalizing Beyond the Attack Used During Training (2019) (3)
- Energy Functionals for Manifold-valued Mappings and Their Properties (2008) (3)
- Provably Adversarially Robust Nearest Prototype Classifiers (2022) (3)
- Confidence-Calibrated Adversarial Training and Detection: More Robust Models Generalizing Beyond the Attack Used During Training (2019) (3)
- Fixing Asymptotic Uncertainty of Bayesian Neural Networks with Infinite ReLU Features (2020) (2)
- Robust sparse recovery with non-negativity constraints (2011) (2)
- MeDeCom: discovery and quantification of latent components of heterogeneous methylomes (2017) (2)
- On the interplay of adversarial robustness and architecture components: patches, convolution and attention (2022) (2)
- K2S Challenge: From Undersampled K-Space to Automatic Segmentation (2023) (2)
- The Global Convergence of the Nonlinear Power Method for Mixed-Subordinate Matrix Norms (2021) (2)
- Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet (2022) (2)
- Direct calculation of depth of correlation and weighting function in ?PIV from experimental particle images (2013) (1)
- Sound Randomized Smoothing in Floating-Point Arithmetics (2022) (1)
- On Mitigating Random and Adversarial Bit Errors (2020) (1)
- Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361) (2015) (1)
- Supplementary Material for Relating Adversarially Robust Generalization to Flat Minima (2021) (1)
- Mini-Workshop: Discrete p-Laplacians: Spectral Theory and Variational Methods in Mathematics and Computer Science (2015) (1)
- Video Segmentation with Graph Cuts (2014) (0)
- A modern look at the relationship between sharpness and generalization (2023) (0)
- Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free (2022) (0)
- Aggregation of Multiple Clusterings and Active Learning in a Transductive Setting (2012) (0)
- Simplex Coding and Supervised Dictionary Learning (2012) (0)
- Nodal domain theorem for the graph p-Laplacian (2016) (0)
- Optimization Algorithms in the Reconstruction of MR Images: A Comparative Study (2011) (0)
- Supplement to ’ Matrix factorization with Binary Components ’ (2013) (0)
- Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291) (2011) (0)
- Lost in Translation: Modern Image Classifiers still degrade even under simple Translations (2022) (0)
- Sparse Dictionary Learning with Simplex Constraints and Application to Topic Modeling (2012) (0)
- A Tensor Block Coordinate Ascent Framework for Hyper Graph Matching (2015) (0)
- Clustering and Community Detection in Signed Networks (2015) (0)
- Sparse recovery for Protein Mass Spectrometry data (2010) (0)
- Robust Principal Component Analysis Based on the Trimmed Component Wise Reconstruction Error (2015) (0)
- Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models (2023) (0)
- CONFIDENCE-CALIBRATED ADVERSARIAL TRAINING (2019) (0)
- HE LOSS SURFACE AND EXPRESSIVITY OF DEEP CONVOLUTIONAL NEURAL NETWORKS (2018) (0)
- Guest Editorial – EuMW Special Issue (2018) (0)
- Neural Network Heuristic Functions: Taking Confidence into Account (2022) (0)
- Weakly Supervised Object Boundaries Supplementary material (2016) (0)
- MRF volume 3 issue 2 Cover and Back matter (2011) (0)
- COMMUNITY DETECTION IN NETWORKS VIA NONLINEAR (2018) (0)
- Nonlinear Spectral Methods for Nonconvex Optimization with Global Optimality (2016) (0)
- Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks (2019) (0)
- German Pattern Recognition Award 2011 Laudatio for Prof . Dr . (2012) (0)
- FONTS True Manifold FONTS Learned Manifold EMNIST Learned Manifold F-MNIST Learned Manifold CelebA (0)
- Thin-Plate Splines Between Riemannian Manifolds (2008) (0)
- T HE LOSS SURFACE AND EXPRESSIVITY OF DEEP CONVOLUTIONAL NEURAL NETWORKS (2017) (0)
- Classifiers Should Do Well Even on Their Worst Classes (2022) (0)
- Large-scale antibody profiling of human blood sera: The future of molecular diagnosis (2009) (0)
- Pattern Recognition : 35th German Conference, GCPR 2013, Saarbrücken, Germany, September 3-6, 2013. Proceedings (2013) (0)
- Clustering-based Audio Segmentation with Applications to Music Structure Analysis (2009) (0)
- Supplementary Material for Disentangling Adversarial Robustness and Generalization (2019) (0)
- Overview of Talks Convex Risks , Calibrated Surrogates , Consistency , and Their Relationship with Nonparametric Estimation (2016) (0)
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