Hofmann, Thomas

117 publications

AISTATS 2025 Emergence of Globally Attracting Fixed Points in Deep Neural Networks with Nonlinear Activations Amir Joudaki, Thomas Hofmann

ICML 2025 Generalized Interpolating Discrete Diffusion Dimitri Von Rütte, Janis Fluri, Yuhui Ding, Antonio Orvieto, Bernhard Schölkopf, Thomas Hofmann

WACV 2025 LIME: Localized Image Editing via Attention Regularization in Diffusion Models Enis Simsar, Alessio Tonioni, Yongqin Xian, Thomas Hofmann, Federico Tombari

CVPR 2025 LoRACLR: Contrastive Adaptation for Customization of Diffusion Models Enis Simsar, Thomas Hofmann, Federico Tombari, Pinar Yanardag

AAAI 2025 On the Expressiveness and Length Generalization of Selective State Space Models on Regular Languages Aleksandar Terzic, Michael Hersche, Giacomo Camposampiero, Thomas Hofmann, Abu Sebastian, Abbas Rahimi

ICML 2025 Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment Yuhui Ding, Thomas Hofmann

NeurIPS 2025 Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models Aleksandar Terzic, Nicolas Menet, Michael Hersche, Thomas Hofmann, Abbas Rahimi

ICLR 2025 The Directionality of Optimization Trajectories in Neural Networks Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf

ICML 2025 The Importance of Being Lazy: Scaling Limits of Continual Learning Jacopo Graldi, Alessandro Breccia, Giulia Lanzillotta, Thomas Hofmann, Lorenzo Noci

NeurIPS 2025 The Non-Linear Representation Dilemma: Is Causal Abstraction Enough for Mechanistic Interpretability? Denis Sutter, Julian Minder, Thomas Hofmann, Tiago Pimentel

ICCV 2025 UIP2P: Unsupervised Instruction-Based Image Editing via Edit Reversibility Constraint Enis Simsar, Alessio Tonioni, Yongqin Xian, Thomas Hofmann, Federico Tombari

ICLRW 2024 A Language Model's Guide Through Latent Space Dimitri von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

ICML 2024 A Language Model’s Guide Through Latent Space Dimitri Von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

ECCVW 2024 An Art-Centric Perspective on AI-Based Content Moderation of Nudity Piera Riccio, Georgina Curto, Thomas Hofmann, Nuria Oliver

ICMLW 2024 Closed Form of the Hessian Spectrum for Some Neural Networks Sidak Pal Singh, Thomas Hofmann

NeurIPSW 2024 Exploring the Limits of Feature Learning in Continual Learning Jacopo Graldi, Giulia Lanzillotta, Lorenzo Noci, Benjamin F Grewe, Thomas Hofmann

ICMLW 2024 Feature Learning Dynamics Under Grokking in a Sparse Parity Task Javier Sanguino Bautiste, Gregor Bachmann, Bobby He, Lorenzo Noci, Thomas Hofmann

ICMLW 2024 Hallmarks of Optimization Trajectories in Neural Networks and LLMs: Directional Exploration and Redundancy Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf

AISTATS 2024 How Good Is a Single Basin? Kai Lion, Lorenzo Noci, Thomas Hofmann, Gregor Bachmann

ICMLW 2024 Landscaping Linear Mode Connectivity Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann

CoLLAs 2024 Local vs Global Continual Learning Giulia Lanzillotta, Sidak Pal Singh, Benjamin F Grewe, Thomas Hofmann

ICML 2024 Navigating Scaling Laws: Compute Optimality in Adaptive Model Training Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag, Thomas Hofmann

ICML 2024 Recurrent Distance Filtering for Graph Representation Learning Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann

ICLR 2024 Simplifying Transformer Blocks Bobby He, Thomas Hofmann

NeurIPS 2024 Super Consistency of Neural Network Landscapes and Learning Rate Transfer Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto

NeurIPSW 2024 Testing Knowledge Distillation Theories with Dataset Size Giulia Lanzillotta, Felix Sarnthein, Gil Kur, Thomas Hofmann, Bobby He

NeurIPSW 2024 Testing the Limits of Data Efficiency in Experience Replay Damiano Meier, Giulia Lanzillotta, Thomas Hofmann

ICLR 2024 Towards Meta-Pruning via Optimal Transport Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh

ICLR 2024 Transformer Fusion with Optimal Transport Moritz Imfeld, Jacopo Graldi, Marco Giordano, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh

ICMLW 2024 Understanding and Minimising Outlier Features in Neural Network Training Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann

ICMLW 2024 Understanding and Minimising Outlier Features in Neural Network Training Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann

NeurIPS 2024 Understanding and Minimising Outlier Features in Transformer Training Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann

CVPR 2023 Achieving a Better Stability-Plasticity Trade-Off via Auxiliary Networks in Continual Learning Sanghwan Kim, Lorenzo Noci, Antonio Orvieto, Thomas Hofmann

CVPRW 2023 CLIP-Guided Vision-Language Pre-Training for Question Answering in 3D Scenes Maria Parelli, Alexandros Delitzas, Nikolas Hars, Georgios Vlassis, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

NeurIPSW 2023 Disentangling Linear Mode Connectivity Gül Sena Altıntaş, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

NeurIPS 2023 Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann

NeurIPSW 2023 Escaping Random Teacher Initialization Enhances Signal Propagation and Representation Felix Sarnthein, Sidak Pal Singh, Antonio Orvieto, Thomas Hofmann

ICLRW 2023 Explaintable: Explaining Large Scale Models Applied to Tabular Data Javier Sanguino Bautiste, Tim Engelmann, Natalia Pato Montemayor, Louis Hart, Giulia Lanzillotta, Gregor Bachmann, Thomas Hofmann

ICLR 2023 FIGARO: Controllable Music Generation Using Learned and Expert Features Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann

NeurIPSW 2023 Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization Elior Benarous, Sotiris Anagnostidis, Luca Biggio, Thomas Hofmann

NeurIPSW 2023 How Good Is a Single Basin? Kai Lion, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

ICCV 2023 Mastering Spatial Graph Prediction of Road Networks Anagnostidis Sotiris, Aurelien Lucchi, Thomas Hofmann

NeurIPSW 2023 Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-Symbolic Architectures Michael Hersche, Francesco di Stefano, Thomas Hofmann, Abu Sebastian, Abbas Rahimi

ICML 2023 Random Teachers Are Good Teachers Felix Sarnthein, Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann

NeurIPS 2023 Scaling MLPs: A Tale of Inductive Bias Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann

ICLR 2023 The Curious Case of Benign Memorization Sotiris Anagnostidis, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

ICML 2023 The Hessian Perspective into the Nature of Convolutional Neural Networks Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf

NeurIPS 2023 The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit Lorenzo Noci, Chuning Li, Mufan Li, Bobby He, Thomas Hofmann, Chris J Maddison, Dan Roy

AISTATS 2022 Vanishing Curvature in Randomly Initialized Deep ReLU Networks Antonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurelien Lucchi

NeurIPSW 2022 Achieving a Better Stability-Plasticity Trade-Off via Auxiliary Networks in Continual Learning Sanghwan Kim, Lorenzo Noci, Antonio Orvieto, Thomas Hofmann

TMLR 2022 Boosting Search Engines with Interactive Agents Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher, Sascha Rothe, Pier Giuseppe Sessa, Lierni Sestorain

ICLR 2022 Generalization Through the Lens of Leave-One-Out Error Gregor Bachmann, Thomas Hofmann, Aurelien Lucchi

ICML 2022 How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

NeurIPS 2022 OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters Piera Riccio, Bill Psomas, Francesco Galati, Francisco Escolano, Thomas Hofmann, Nuria Oliver

ICLR 2022 Phenomenology of Double Descent in Finite-Width Neural Networks Sidak Pal Singh, Aurelien Lucchi, Thomas Hofmann, Bernhard Schölkopf

AISTATS 2021 Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand, Thomas Hofmann, Roy S. Smith

NeurIPS 2021 Analytic Insights into Structure and Rank of Neural Network Hessian Maps Sidak Pal Singh, Gregor Bachmann, Thomas Hofmann

NeurIPS 2021 Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann

ICCV 2021 Learning Generative Models of Textured 3D Meshes from Real-World Images Dario Pavllo, Jonas Kohler, Thomas Hofmann, Aurelien Lucchi

NeurIPS 2021 Precise Characterization of the Prior Predictive Distribution of Deep ReLU Networks Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann

ICML 2021 Uniform Convergence, Adversarial Spheres and a Simple Remedy Gregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann

NeurIPS 2020 Adversarial Training Is a Form of Data-Dependent Operator Norm Regularization Kevin Roth, Yannic Kilcher, Thomas Hofmann

NeurIPS 2020 Batch Normalization Provably Avoids Ranks Collapse for Randomly Initialised Deep Networks Hadi Daneshmand, Jonas Kohler, Francis R. Bach, Thomas Hofmann, Aurelien Lucchi

ECCV 2020 Controlling Style and Semantics in Weakly-Supervised Image Generation Dario Pavllo, Aurelien Lucchi, Thomas Hofmann

NeurIPS 2020 Convolutional Generation of Textured 3D Meshes Dario Pavllo, Graham Spinks, Thomas Hofmann, Marie-Francine Moens, Aurelien Lucchi

AAAI 2020 LeDeepChef Deep Reinforcement Learning Agent for Families of Text-Based Games Leonard Adolphs, Thomas Hofmann

NeurIPS 2019 A Domain Agnostic Measure for Monitoring and Evaluating GANs Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi, Nathanael Perraudin, Ian Goodfellow, Thomas Hofmann, Andreas Krause

AISTATS 2019 Exponential Convergence Rates for Batch Normalization: The Power of Length-Direction Decoupling in Non-Convex Optimization Jonas Kohler, Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann, Ming Zhou, Klaus Neymeyr

AISTATS 2019 Local Saddle Point Optimization: A Curvature Exploitation Approach Leonard Adolphs, Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann

ICML 2019 The Odds Are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth, Yannic Kilcher, Thomas Hofmann

ICML 2018 A Distributed Second-Order Algorithm You Can Trust Celestine Duenner, Aurelien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi

ICLR 2018 An Online Learning Approach to Generative Adversarial Networks Paulina Grnarova, Kfir Y Levy, Aurelien Lucchi, Thomas Hofmann, Andreas Krause

NeurIPS 2018 Deep State Space Models for Unconditional Word Generation Florian Schmidt, Thomas Hofmann

ICML 2018 Escaping Saddles with Stochastic Gradients Hadi Daneshmand, Jonas Kohler, Aurelien Lucchi, Thomas Hofmann

ICML 2018 Hyperbolic Entailment Cones for Learning Hierarchical Embeddings Octavian Ganea, Gary Becigneul, Thomas Hofmann

NeurIPS 2018 Hyperbolic Neural Networks Octavian Ganea, Gary Becigneul, Thomas Hofmann

ICLR 2018 Semantic Interpolation in Implicit Models Yannic Kilcher, Aurelien Lucchi, Thomas Hofmann

NeurIPS 2017 Stabilizing Training of Generative Adversarial Networks Through Regularization Kevin Roth, Aurelien Lucchi, Sebastian Nowozin, Thomas Hofmann

NeurIPS 2016 Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy Aryan Mokhtari, Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann, Alejandro Ribeiro

ICML 2016 Starting Small - Learning with Adaptive Sample Sizes Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann

NeurIPS 2015 Variance Reduced Stochastic Gradient Descent with Neighbors Thomas Hofmann, Aurelien Lucchi, Simon Lacoste-Julien, Brian McWilliams

NeurIPS 2014 Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi, Virginia Smith, Martin Takac, Jonathan Terhorst, Sanjay Krishnan, Thomas Hofmann, Michael I Jordan

ECML-PKDD 2011 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part II Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis

ECML-PKDD 2011 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis

ECML-PKDD 2011 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part I Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis

CVPR 2008 Beyond Sliding Windows: Object Localization by Efficient Subwindow Search Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann

IJCAI 2007 Exploiting Known Taxonomies in Learning Overlapping Concepts Lijuan Cai, Thomas Hofmann

ICML 2005 A Brain Computer Interface with Online Feedback Based on Magnetoencephalography Thomas Navin Lal, Michael Schröder, N. Jeremy Hill, Hubert Preißl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer, Bernhard Schölkopf

AISTATS 2005 Kernel Methods for Missing Variables Alex J. Smola, S. V. N. Vishwanathan, Thomas Hofmann

JMLR 2005 Large Margin Methods for Structured and Interdependent Output Variables Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun

UAI 2004 Exponential Families for Conditional Random Fields Yasemin Altun, Alexander J. Smola, Thomas Hofmann

ICML 2004 Gaussian Process Classification for Segmenting and Annotating Sequences Yasemin Altun, Thomas Hofmann, Alexander J. Smola

COLT 2004 Learning over Compact Metric Spaces Ha Quang Minh, Thomas Hofmann

NeurIPS 2004 Semi-Supervised Learning on Directed Graphs Dengyong Zhou, Thomas Hofmann, Bernhard Schölkopf

ICML 2004 Support Vector Machine Learning for Interdependent and Structured Output Spaces Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, Yasemin Altun

ICML 2004 Unifying Collaborative and Content-Based Filtering Justin Basilico, Thomas Hofmann

ICML 2003 Hidden Markov Support Vector Machines Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofmann

IJCAI 2003 Hierarchical Semantic Classification: Word Sense Disambiguation with World Knowledge Massimiliano Ciaramita, Thomas Hofmann, Mark Johnson

NeurIPS 2003 Multiple Instance Learning via Disjunctive Programming Boosting Stuart Andrews, Thomas Hofmann

NeurIPS 2002 Discriminative Learning for Label Sequences via Boosting Yasemin Altun, Thomas Hofmann, Mark Johnson

AAAI 2002 Multiple Instance Learning with Generalized Support Vector Machines Stuart Andrews, Thomas Hofmann, Ioannis Tsochantaridis

NeurIPS 2002 Support Vector Machines for Multiple-Instance Learning Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann

ECML-PKDD 2002 Support Vector Machines for Polycategorical Classification Ioannis Tsochantaridis, Thomas Hofmann

ECML-PKDD 2001 Learning What People (Don't) Want Thomas Hofmann

MLJ 2001 Unsupervised Learning by Probabilistic Latent Semantic Analysis Thomas Hofmann

ICML 2000 Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval Keith B. Hall, Thomas Hofmann

NeurIPS 2000 The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity David A. Cohn, Thomas Hofmann

CVPR 1999 Histogram Clustering for Unsupervised Image Segmentation Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann

IJCAI 1999 Latent Class Models for Collaborative Filtering Thomas Hofmann, Jan Puzicha

NeurIPS 1999 Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization Thomas Hofmann

UAI 1999 Probabilistic Latent Semantic Analysis Thomas Hofmann

IJCAI 1999 The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data Thomas Hofmann

NeurIPS 1998 Learning from Dyadic Data Thomas Hofmann, Jan Puzicha, Michael I. Jordan

NeurIPS 1997 Active Data Clustering Thomas Hofmann, Joachim M. Buhmann

CVPR 1997 Non-Parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann

NeurIPS 1994 Multidimensional Scaling and Data Clustering Thomas Hofmann, Joachim Buhmann

NeurIPS 1993 Central and Pairwise Data Clustering by Competitive Neural Networks Joachim Buhmann, Thomas Hofmann