Central and Pairwise Data Clustering by Competitive Neural Networks. - Joachim M. Buhmann; Thomas Hofmann 001 (NIPS, 1993)

A maximum entropy approach to pairwise data clustering. - Joachim M. Buhmann; Thomas Hofmann 001 (ICPR (2), 1994)

Multidimensional Scaling and Data Clustering. - Thomas Hofmann 001; Joachim M. Buhmann (NIPS, 1994)

The Mobile Robot RHINO. - Joachim M. Buhmann; Wolfram Burgard; Armin B. Cremers; Dieter Fox; Thomas Hofmann 001; Frank E. Schneider; Jiannis Strikos; Sebastian Thrun (AI Mag., 1995)

An Annealed "Neural Gas" Network for Robust Vector Quantization. - Thomas Hofmann 001; Joachim M. Buhmann (ICANN, 1996)

Unsupervised segmentation of textured images by pairwise data clustering. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (ICIP (3), 1996)

Inferring Hierarchical Clustering Structures by Deterministic Annealing. - Thomas Hofmann 001; Joachim M. Buhmann (KDD, 1996)

Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval. - Jan Puzicha; Thomas Hofmann 001; Joachim M. Buhmann (CVPR, 1997)

Deterministic Annealing for Unsupervised Texture Segmentation. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (EMMCVPR, 1997)

Robust vector quantization by competitive learning. - Joachim M. Buhmann; Thomas Hofmann 001 (ICASSP, 1997)

An Optimization Approach to Unsupervised Hierarchical Texture Segmentation. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (ICIP (3), 1997)

Active Data Clustering. - Thomas Hofmann 001; Joachim M. Buhmann (NIPS, 1997)

Pairwise Data Clustering by Deterministic Annealing. - Thomas Hofmann 001; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 1997)

Correction to "Pairwise Data Clustering by Deterministic Annealing". - Thomas Hofmann 001; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 1997)

Data clustering and beyond: a deterministic annealing framework for exploratory data analysis. - Thomas Hofmann 001 (Shaker, 1997)

Discrete Mixture Models for Unsupervised Image Segmentation. - Jan Puzicha; Joachim M. Buhmann; Thomas Hofmann 001 (DAGM-Symposium, 1998)

Mixture models for co-occurrence and histogram data. - Thomas Hofmann 001; Jan Puzicha (ICPR, 1998)

Learning from Dyadic Data. - Thomas Hofmann 001; Jan Puzicha; Michael I. Jordan (NIPS, 1998)

Unsupervised Texture Segmentation in a Deterministic Annealing Framework. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 1998)

Competitive learning algorithms for robust vector quantization. - Thomas Hofmann 001; Joachim M. Buhmann (IEEE Trans. Signal Process., 1998)

Histogram Clustering for Unsupervised Image Segmentation. - Jan Puzicha; Joachim M. Buhmann; Thomas Hofmann 001 (CVPR, 1999)

Probabilistic Topic Maps: Navigating through Large Text Collections. - Thomas Hofmann 001 (IDA, 1999)

The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data. - Thomas Hofmann 001 (IJCAI, 1999)

Latent Class Models for Collaborative Filtering. - Thomas Hofmann 001; Jan Puzicha (IJCAI, 1999)

Topic-based language models using EM. - Daniel Gildea; Thomas Hofmann 001 (EUROSPEECH, 1999)

Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization. - Thomas Hofmann 001 (NIPS, 1999)

Probabilistic Latent Semantic Analysis. - Thomas Hofmann 001 (UAI, 1999)

Histogram clustering for unsupervised segmentation and image retrieval. - Jan Puzicha; Thomas Hofmann 001; Joachim M. Buhmann (Pattern Recognit. Lett., 1999)

OpenSpaces: An Object-Oriented Framework for Reconfigurable Coordination Spaces. - Stéphane Ducasse; Thomas Hofmann 001; Oscar Nierstrasz (COORDINATION, 2000)

Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval. - Keith B. Hall; Thomas Hofmann 001 (ICML, 2000)

The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity. - David A. Cohn; Thomas Hofmann 001 (NIPS, 2000)

Learning probabilistic models of the Web. - Thomas Hofmann 001 (SIGIR, 2000)

ProbMap - A probabilistic approach for mapping large document collections. - Thomas Hofmann 001 (Intell. Data Anal., 2000)

A theory of proximity based clustering: structure detection by optimization. - Jan Puzicha; Thomas Hofmann 001; Joachim M. Buhmann (Pattern Recognit., 2000)

Text Classification in a Hierarchical Mixture Model for Small Training Sets. - Kristina Toutanova; Francine Chen 001; Kris Popat; Thomas Hofmann 001 (CIKM, 2001)

Learning What People (Don't) Want. - Thomas Hofmann 001 (ECML, 2001)

Unsupervised Learning by Probabilistic Latent Semantic Analysis. - Thomas Hofmann 001 (Mach. Learn., 2001)

Multiple Instance Learning with Generalized Support Vector Machines. - Stuart Andrews; Thomas Hofmann 001; Ioannis Tsochantaridis (AAAI/IAAI, 2002)

Support Vector Machines for Polycategorical Classification. - Ioannis Tsochantaridis; Thomas Hofmann 001 (ECML, 2002)

Discriminative Learning for Label Sequences via Boosting. - Yasemin Altun; Thomas Hofmann 001; Mark Johnson 001 (NIPS, 2002)

Support Vector Machines for Multiple-Instance Learning. - Stuart Andrews; Ioannis Tsochantaridis; Thomas Hofmann 001 (NIPS, 2002)

Predicting CNS Permeability of Drug Molecules: Comparison of Neural Network and Support Vector Machine Algorithms. - Scott Doniger; Thomas Hofmann 001; Miao-Hui Joanne Yeh (J. Comput. Biol., 2002)

Investigating Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences. - Yasemin Altun; Mark Johnson 001; Thomas Hofmann 001 (EMNLP, 2003)

Hidden Markov Support Vector Machines. - Yasemin Altun; Ioannis Tsochantaridis; Thomas Hofmann 001 (ICML, 2003)

Hierarchical Semantic Classification: Word Sense Disambiguation with World Knowledge. - Massimiliano Ciaramita; Thomas Hofmann 001; Mark Johnson 001 (IJCAI, 2003)

Large margin methods for label sequence learning. - Yasemin Altun; Thomas Hofmann 001 (INTERSPEECH, 2003)

Phaszination Ergonomie: Von der Entlastung am Fließband zur Inspiration im Design. - Claudius Lazzeroni; Petra Gersch; Thomas Hofmann 001; Christian Noss (UP, 2003)

Multiple-Instance Learning via Disjunctive Programming Boosting. - Stuart Andrews; Thomas Hofmann 001 (NIPS, 2003)

Text categorization by boosting automatically extracted concepts. - Lijuan Cai; Thomas Hofmann 001 (SIGIR, 2003)

Collaborative filtering via gaussian probabilistic latent semantic analysis. - Thomas Hofmann 001 (SIGIR, 2003)

Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002. - James Allan; Jay Aslam; Nicholas J. Belkin; Chris Buckley; James P. Callan; W. Bruce Croft; Susan T. Dumais; Norbert Fuhr; Donna Harman; David J. Harper; Djoerd Hiemstra; Thomas Hofmann 001; et al. (SIGIR Forum, 2003)

Hierarchical document categorization with support vector machines. - Lijuan Cai; Thomas Hofmann 001 (CIKM, 2004)

Learning Over Compact Metric Spaces. - Ha Quang Minh; Thomas Hofmann 001 (COLT, 2004)

Gaussian process classification for segmenting and annotating sequences. - Yasemin Altun; Thomas Hofmann 001; Alexander J. Smola (ICML, 2004)

Unifying collaborative and content-based filtering. - Justin Basilico; Thomas Hofmann 001 (ICML, 2004)

Support vector machine learning for interdependent and structured output spaces. - Ioannis Tsochantaridis; Thomas Hofmann 001; Thorsten Joachims; Yasemin Altun (ICML, 2004)

Semi-supervised Learning on Directed Graphs. - Dengyong Zhou; Bernhard Schölkopf; Thomas Hofmann 001 (NIPS, 2004)

A joint framework for collaborative and content filtering. - Justin Basilico; Thomas Hofmann 001 (SIGIR, 2004)

Exponential Families for Conditional Random Fields. - Yasemin Altun; Alexander J. Smola; Thomas Hofmann 001 (UAI, 2004)

Latent semantic models for collaborative filtering. - Thomas Hofmann 001 (ACM Trans. Inf. Syst., 2004)

Kernel Methods for Missing Variables. - Alexander J. Smola; S. V. N. Vishwanathan; Thomas Hofmann 001 (AISTATS, 2005)

Collaborative Machine Learning. - Thomas Hofmann 001; Justin Basilico (From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments, 2005)

From bits and bytes to information and knowledge. - Thomas Hofmann 001 (CIKM, 2005)

A brain computer interface with online feedback based on magnetoencephalography. - Thomas Navin Lal; Michael Schröder 002; N. Jeremy Hill; Hubert Preißl; Thilo Hinterberger; Jürgen Mellinger; Martin Bogdan; Wolfgang Rosenstiel; Thomas Hofmann 001; Niels Birbaumer; Bernhard Schölkopf (ICML, 2005)

Non-redundant clustering with conditional ensembles. - David Gondek; Thomas Hofmann 001 (KDD, 2005)

Large Margin Methods for Structured and Interdependent Output Variables. - Ioannis Tsochantaridis; Thorsten Joachims; Thomas Hofmann 001; Yasemin Altun (J. Mach. Learn. Res., 2005)

Global Biclustering of Microarray Data. - Thomas Wolf; Benedikt Brors; Thomas Hofmann 001; Elisabeth Georgii (ICDM Workshops, 2006)

Cross System Personalization and Collaborative Filtering by Learning Manifold Alignments. - Bhaskar Mehta; Thomas Hofmann 001 (KI, 2006)

Exploiting Known Taxonomies in Learning Overlapping Concepts. - Lijuan Cai; Thomas Hofmann 001 (IJCAI, 2007)

Lies and propaganda: detecting spam users in collaborative filtering. - Bhaskar Mehta; Thomas Hofmann 001; Peter Fankhauser (IUI, 2007)

Robust collaborative filtering. - Bhaskar Mehta; Thomas Hofmann 001; Wolfgang Nejdl (RecSys, 2007)

Non-redundant data clustering. - David Gondek; Thomas Hofmann 001 (Knowl. Inf. Syst., 2007)

Advanced experimental and numerical methods for the analysis of the dynamic forming press behavior. - Peter Groche; Knut Großmann; Thomas Hofmann 001; Hajo Wiemer (Prod. Eng., 2007)

Beyond sliding windows: Object localization by efficient subwindow search. - Christoph H. Lampert; Matthew B. Blaschko; Thomas Hofmann 001 (CVPR, 2008)

NEW HMI Möglichkeiten und Grenzen abstrakt-geographischer Visualisierung in Bereich der Anlagensteuerung. - Thomas Hofmann 001; Peter Holzkämper (UP, 2008)

Evaluation eines Human-Machine-Interface für Tower-Fluglotsen unter Einsatz eines Simulators. - Christina König; Thomas Hofmann 001; Jörg Bergner; Ralph Bruder (UP, 2008)

A Survey of Attack-Resistant Collaborative Filtering Algorithms. - Bhaskar Mehta; Thomas Hofmann 001 (IEEE Data Eng. Bull., 2008)

Inkrementelle nutzergerechte Etablierung eines Towerlotsen-HMI. - Christina König; Thomas Hofmann 001; Jörg Bergner; Ralph Bruder (MuC, 2009)

Predicting structured objects with support vector machines. - Thorsten Joachims; Thomas Hofmann 001; Yisong Yue; Chun-Nam John Yu (Commun. ACM, 2009)

Efficient Subwindow Search: A Branch and Bound Framework for Object Localization. - Christoph H. Lampert; Matthew B. Blaschko; Thomas Hofmann 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Communication-Efficient Distributed Dual Coordinate Ascent. - Martin Jaggi; Virginia Smith; Martin Takác 001; Jonathan Terhorst; Sanjay Krishnan; Thomas Hofmann 001; Michael I. Jordan (NIPS, 2014)

Exploiting Document Content for Efficient Aggregation of Crowdsourcing Votes. - Martin Davtyan; Carsten Eickhoff; Thomas Hofmann 001 (CIKM, 2015)

Variance Reduced Stochastic Gradient Descent with Neighbors. - Thomas Hofmann 001; Aurélien Lucchi; Simon Lacoste-Julien; Brian McWilliams (NIPS, 2015)

Modelling Term Dependence with Copulas. - Carsten Eickhoff; Arjen P. de Vries; Thomas Hofmann 001 (SIGIR, 2015)

Neighborhood Watch: Stochastic Gradient Descent with Neighbors. - Thomas Hofmann 001; Aurélien Lucchi; Brian McWilliams (CoRR, 2015)

A Variance Reduced Stochastic Newton Method. - Aurélien Lucchi; Brian McWilliams; Thomas Hofmann 001 (CoRR, 2015)

Active Content-Based Crowdsourcing Task Selection. - Piyush Bansal; Carsten Eickhoff; Thomas Hofmann 001 (CIKM, 2016)

Audio Based Bird Species Identification using Deep Learning Techniques. - Elias Sprengel; Martin Jaggi; Yannic Kilcher; Thomas Hofmann 001 (CLEF (Working Notes), 2016)

Starting Small - Learning with Adaptive Sample Sizes. - Hadi Daneshmand; Aurélien Lucchi; Thomas Hofmann 001 (ICML, 2016)

DFS- ConceptDesk - Experimenteller Workspace für Fluglotsen. - Thomas Hofmann 001; Jörg Bergner (UP, 2016)

Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy. - Aryan Mokhtari; Hadi Daneshmand; Aurélien Lucchi; Thomas Hofmann 001; Alejandro Ribeiro (NIPS, 2016)

Probabilistic Bag-Of-Hyperlinks Model for Entity Linking. - Octavian-Eugen Ganea; Marina Ganea; Aurélien Lucchi; Carsten Eickhoff; Thomas Hofmann 001 (WWW, 2016)

Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning. - Wenhu Chen; Aurélien Lucchi; Thomas Hofmann 001 (CoRR, 2016)

DynaNewton - Accelerating Newton's Method for Machine Learning. - Hadi Daneshmand; Aurélien Lucchi; Thomas Hofmann 001 (CoRR, 2016)

Semantic Place Descriptors for Classification and Map Discovery. - Siddharth Sarda; Carsten Eickhoff; Thomas Hofmann 001 (CoRR, 2016)

Deep Joint Entity Disambiguation with Local Neural Attention. - Octavian-Eugen Ganea; Thomas Hofmann 001 (EMNLP, 2017)

Stabilizing Training of Generative Adversarial Networks through Regularization. - Kevin Roth; Aurélien Lucchi; Sebastian Nowozin; Thomas Hofmann 001 (NIPS, 2017)

Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification. - Jan Deriu; Aurélien Lucchi; Valeria De Luca; Aliaksei Severyn; Simon Müller; Mark Cieliebak; Thomas Hofmann 001; Martin Jaggi (WWW, 2017)

Accelerated Dual Learning by Homotopic Initialization. - Hadi Daneshmand; Hamed Hassani; Thomas Hofmann 001 (CoRR, 2017)

Generator Reversal. - Yannic Kilcher; Aurélien Lucchi; Thomas Hofmann 001 (CoRR, 2017)

Flexible Prior Distributions for Deep Generative Models. - Yannic Kilcher; Aurélien Lucchi; Thomas Hofmann 001 (CoRR, 2017)

Parametrizing filters of a CNN with a GAN. - Yannic Kilcher; Gary Bécigneul; Thomas Hofmann 001 (CoRR, 2017)

The best defense is a good offense: Countering black box attacks by predicting slightly wrong labels. - Yannic Kilcher; Thomas Hofmann 001 (CoRR, 2017)

Probabilistic Latent Semantic Indexing. - Thomas Hofmann 001 (SIGIR Forum, 2017)

Fully Character-Level Neural Machine Translation without Explicit Segmentation. - Jason Lee 002; Kyunghyun Cho; Thomas Hofmann 001 (Trans. Assoc. Comput. Linguistics, 2017)

Learning Aerial Image Segmentation From Online Maps. - Pascal Kaiser; Jan Dirk Wegner; Aurélien Lucchi; Martin Jaggi; Thomas Hofmann 001; Konrad Schindler (IEEE Trans. Geosci. Remote. Sens., 2017)

End-to-End Neural Entity Linking. - Nikolaos Kolitsas; Octavian-Eugen Ganea; Thomas Hofmann 001 (CoNLL, 2018)

Learning and Evaluating Sparse Interpretable Sentence Embeddings. - Valentin Trifonov; Octavian-Eugen Ganea; Anna Potapenko; Thomas Hofmann 001 (BlackboxNLP@EMNLP, 2018)

An Online Learning Approach to Generative Adversarial Networks. - Paulina Grnarova; Kfir Y. Levy; Aurélien Lucchi; Thomas Hofmann 001; Andreas Krause 001 (ICLR (Poster), 2018)

Semantic Interpolation in Implicit Models. - Yannic Kilcher; Aurélien Lucchi; Thomas Hofmann 001 (ICLR (Poster), 2018)

Escaping Saddles with Stochastic Gradients. - Hadi Daneshmand; Jonas Moritz Kohler; Aurélien Lucchi; Thomas Hofmann 001 (ICML, 2018)

A Distributed Second-Order Algorithm You Can Trust. - Celestine Dünner; Aurélien Lucchi; Matilde Gargiani; An Bian; Thomas Hofmann 001; Martin Jaggi (ICML, 2018)

Hyperbolic Entailment Cones for Learning Hierarchical Embeddings. - Octavian-Eugen Ganea; Gary Bécigneul; Thomas Hofmann 001 (ICML, 2018)

Hyperbolic Neural Networks. - Octavian-Eugen Ganea; Gary Bécigneul; Thomas Hofmann 001 (NeurIPS, 2018)

Deep State Space Models for Unconditional Word Generation. - Florian Schmidt 005; Thomas Hofmann 001 (NeurIPS, 2018)

Adversarially Robust Training through Structured Gradient Regularization. - Kevin Roth; Aurélien Lucchi; Sebastian Nowozin; Thomas Hofmann 001 (CoRR, 2018)

Zero-Shot Dual Machine Translation. - Lierni Sestorain; Massimiliano Ciaramita; Christian Buck; Thomas Hofmann 001 (CoRR, 2018)

Towards a Theoretical Understanding of Batch Normalization. - Jonas Moritz Kohler; Hadi Daneshmand; Aurélien Lucchi; Ming Zhou 007; Klaus Neymeyr; Thomas Hofmann 001 (CoRR, 2018)

Evaluating GANs via Duality. - Paulina Grnarova; Kfir Y. Levy; Aurélien Lucchi; Nathanaël Perraudin; Thomas Hofmann 001; Andreas Krause 001 (CoRR, 2018)

Local Saddle Point Optimization: A Curvature Exploitation Approach. - Leonard Adolphs; Hadi Daneshmand; Aurélien Lucchi; Thomas Hofmann 001 (AISTATS, 2019)

Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization. - Jonas Moritz Kohler; Hadi Daneshmand; Aurélien Lucchi; Thomas Hofmann 001; Ming Zhou 007; Klaus Neymeyr (AISTATS, 2019)

Autoregressive Text Generation Beyond Feedback Loops. - Florian Schmidt 005; Stephan Mandt; Thomas Hofmann 001 (EMNLP/IJCNLP (1), 2019)

The Odds are Odd: A Statistical Test for Detecting Adversarial Examples. - Kevin Roth; Yannic Kilcher; Thomas Hofmann 001 (ICML, 2019)

A Domain Agnostic Measure for Monitoring and Evaluating GANs. - Paulina Grnarova; Kfir Y. Levy; Aurélien Lucchi; Nathanaël Perraudin; Ian J. Goodfellow; Thomas Hofmann 001; Andreas Krause 001 (NeurIPS, 2019)

Adversarial Training Generalizes Data-dependent Spectral Norm Regularization. - Kevin Roth; Yannic Kilcher; Thomas Hofmann 001 (CoRR, 2019)

Cosmological N-body simulations: a challenge for scalable generative models. - Nathanaël Perraudin; Ankit Srivastava; Aurélien Lucchi; Tomasz Kacprzak; Thomas Hofmann 001; Alexandre Réfrégier (CoRR, 2019)

Mixing of Stochastic Accelerated Gradient Descent. - Peiyuan Zhang; Hadi Daneshmand; Thomas Hofmann 001 (CoRR, 2019)

LeDeepChef Deep Reinforcement Learning Agent for Families of Text-Based Games. - Leonard Adolphs; Thomas Hofmann 001 (AAAI, 2020)

Controlling Style and Semantics in Weakly-Supervised Image Generation. - Dario Pavllo; Aurélien Lucchi; Thomas Hofmann 001 (ECCV (6), 2020)

Batch normalization provably avoids ranks collapse for randomly initialised deep networks. - Hadi Daneshmand; Jonas Moritz Kohler; Francis R. Bach; Thomas Hofmann 001; Aurélien Lucchi (NeurIPS, 2020)

Convolutional Generation of Textured 3D Meshes. - Dario Pavllo; Graham Spinks; Thomas Hofmann 001; Marie-Francine Moens; Aurélien Lucchi (NeurIPS, 2020)

Adversarial Training is a Form of Data-dependent Operator Norm Regularization. - Kevin Roth; Yannic Kilcher; Thomas Hofmann 001 (NeurIPS, 2020)

Theoretical Understanding of Batch-normalization: A Markov Chain Perspective. - Hadi Daneshmand; Jonas Moritz Kohler; Francis R. Bach; Thomas Hofmann 001; Aurélien Lucchi (CoRR, 2020)

BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward. - Florian Schmidt 005; Thomas Hofmann 001 (CoRR, 2020)

Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization. - Peiyuan Zhang; Antonio Orvieto; Hadi Daneshmand; Thomas Hofmann 001; Roy S. Smith (AISTATS, 2021)

Learning Generative Models of Textured 3D Meshes from Real-World Images. - Dario Pavllo; Jonas Kohler; Thomas Hofmann 001; Aurélien Lucchi (ICCV, 2021)

Uniform Convergence, Adversarial Spheres and a Simple Remedy. - Gregor Bachmann; Seyed-Mohsen Moosavi-Dezfooli; Thomas Hofmann 001 (ICML, 2021)

Precise characterization of the prior predictive distribution of deep ReLU networks. - Lorenzo Noci; Gregor Bachmann; Kevin Roth; Sebastian Nowozin; Thomas Hofmann 001 (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 001 (NeurIPS, 2021)

Analytic Insights into Structure and Rank of Neural Network Hessian Maps. - Sidak Pal Singh; Gregor Bachmann; Thomas Hofmann 001 (NeurIPS, 2021)

SwissDial: Parallel Multidialectal Corpus of Spoken Swiss German. - Pelin Dogan-Schönberger; Julian Mäder; Thomas Hofmann 001 (CoRR, 2021)

Generative Minimization Networks: Training GANs Without Competition. - Paulina Grnarova; Yannic Kilcher; Kfir Y. Levy; Aurélien Lucchi; Thomas Hofmann 001 (CoRR, 2021)

Vanishing Curvature and the Power of Adaptive Methods in Randomly Initialized Deep Networks. - Antonio Orvieto; Jonas Kohler; Dario Pavllo; Thomas Hofmann 001; Aurélien Lucchi (CoRR, 2021)

How to Query Language Models? - Leonard Adolphs; Shehzaad Dhuliawala; Thomas Hofmann 001 (CoRR, 2021)

Boosting Search Engines with Interactive Agents. - Leonard Adolphs; Benjamin Börschinger; Christian Buck; Michelle Chen Huebscher; Massimiliano Ciaramita; Lasse Espeholt; Thomas Hofmann 001; Yannic Kilcher (CoRR, 2021)

Vanishing Curvature in Randomly Initialized Deep ReLU Networks. - Antonio Orvieto; Jonas Kohler; Dario Pavllo; Thomas Hofmann 001; Aurélien Lucchi (AISTATS, 2022)

Decoding a Neural Retriever's Latent Space for Query Suggestion. - Leonard Adolphs; Michelle Chen Huebscher; Christian Buck; Sertan Girgin; Olivier Bachem; Massimiliano Ciaramita; Thomas Hofmann 001 (EMNLP, 2022)

Generalization Through the Lens of Leave-One-Out Error. - Gregor Bachmann; Thomas Hofmann 001; Aurélien Lucchi (ICLR, 2022)

Phenomenology of Double Descent in Finite-Width Neural Networks. - Sidak Pal Singh; Aurélien Lucchi; Thomas Hofmann 001; Bernhard Schölkopf (ICLR, 2022)

How Tempering Fixes Data Augmentation in Bayesian Neural Networks. - Gregor Bachmann; Lorenzo Noci; Thomas Hofmann 001 (ICML, 2022)

OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters. - Piera Riccio; Bill Psomas; Francesco Galati; Francisco Escolano; Thomas Hofmann 001; Nuria Oliver (NeurIPS, 2022)

Randomized Signature Layers for Signal Extraction in Time Series Data. - Enea Monzio Compagnoni; Luca Biggio; Antonio Orvieto; Thomas Hofmann 001; Josef Teichmann (CoRR, 2022)

Cosmology from Galaxy Redshift Surveys with PointNet. - Sotiris Anagnostidis; Arne Thomsen; Tomasz Kacprzak; Tilman Tröster; Luca Biggio; Alexandre Refregier; Thomas Hofmann 001 (CoRR, 2022)

Boosting Search Engines with Interactive Agents. - Leonard Adolphs; Benjamin Börschinger; Christian Buck; Michelle Chen Huebscher; Massimiliano Ciaramita; Lasse Espeholt; Thomas Hofmann 001; Yannic Kilcher; Sascha Rothe; Pier Giuseppe Sessa; Lierni Sestorain (Trans. Mach. Learn. Res., 2022)

Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes. - Alexandros Delitzas; Maria Parelli; Nikolas Hars; Georgios Vlassis; Sotirios-Konstantinos Anagnostidis; Gregor Bachmann; Thomas Hofmann 001 (BMVC, 2023)

Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning. - Sanghwan Kim; Lorenzo Noci; Antonio Orvieto; Thomas Hofmann 001 (CVPR, 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 001 (CVPR Workshops, 2023)

Mastering Spatial Graph Prediction of Road Networks. - Sotiris Anagnostidis; Aurélien Lucchi; Thomas Hofmann 001 (ICCV, 2023)

The Curious Case of Benign Memorization. - Sotiris Anagnostidis; Gregor Bachmann; Lorenzo Noci; Thomas Hofmann 001 (ICLR, 2023)

FIGARO: Controllable Music Generation using Learned and Expert Features. - Dimitri von Rütte; Luca Biggio; Yannic Kilcher; Thomas Hofmann 001 (ICLR, 2023)

Random Teachers are Good Teachers. - Felix Sarnthein; Gregor Bachmann; Sotiris Anagnostidis; Thomas Hofmann 001 (ICML, 2023)

The Hessian perspective into the Nature of Convolutional Neural Networks. - Sidak Pal Singh; Thomas Hofmann 001; Bernhard Schölkopf (ICML, 2023)

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics. - Enea Monzio Compagnoni; Anna Scampicchio; Luca Biggio; Antonio Orvieto; Thomas Hofmann 001; Josef Teichmann (IJCNN, 2023)

Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers. - Sotiris Anagnostidis; Dario Pavllo; Luca Biggio; Lorenzo Noci; Aurélien Lucchi; Thomas Hofmann 001 (NeurIPS, 2023)

Scaling MLPs: A Tale of Inductive Bias. - Gregor Bachmann; Sotiris Anagnostidis; Thomas Hofmann 001 (NeurIPS, 2023)

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. - Lorenzo Noci; Chuning Li; Mufan Bill Li; Bobby He; Thomas Hofmann 001; Chris J. Maddison; Dan Roy (NeurIPS, 2023)

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. - Lorenzo Noci; Chuning Li; Mufan Bill Li; Bobby He; Thomas Hofmann 001; Chris J. Maddison; Daniel M. Roy 001 (CoRR, 2023)

The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute. - Aleksandar Stanic; Dylan R. Ashley; Oleg Serikov; Louis Kirsch; Francesco Faccio; Jürgen Schmidhuber; Thomas Hofmann 001; Imanol Schlag (CoRR, 2023)

Towards guarantees for parameter isolation in continual learning. - Giulia Lanzillotta; Sidak Pal Singh; Benjamin F. Grewe; Thomas Hofmann 001 (CoRR, 2023)

Navigating Scaling Laws: Accelerating Vision Transformer's Training via Adaptive Strategies. - Sotiris Anagnostidis; Gregor Bachmann; Thomas Hofmann 001 (CoRR, 2023)

Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization. - Elior Benarous; Sotiris Anagnostidis; Luca Biggio; Thomas Hofmann 001 (CoRR, 2023)

Recurrent Distance-Encoding Neural Networks for Graph Representation Learning. - Yuhui Ding; Antonio Orvieto; Bobby He; Thomas Hofmann 001 (CoRR, 2023)

Disentangling Linear Mode-Connectivity. - Gul Sena Altintas; Gregor Bachmann; Lorenzo Noci; Thomas Hofmann 001 (CoRR, 2023)

Causal Estimation of Memorisation Profiles. - Pietro Lesci; Clara Meister; Thomas Hofmann 001; Andreas Vlachos 001; Tiago Pimentel (ACL (1), 2024)

On the Effect of (Near) Duplicate Subwords in Language Modelling. - Anton Schäfer; Thomas Hofmann 001; Imanol Schlag; Tiago Pimentel (ACL (Findings), 2024)

How Good is a Single Basin? - Kai Lion; Lorenzo Noci; Thomas Hofmann 001; Gregor Bachmann (AISTATS, 2024)

Exposed or Erased: Algorithmic Censorship of Nudity in Art. - Piera Riccio; Thomas Hofmann 001; Nuria Oliver (CHI, 2024)

Local vs Global continual learning. - Giulia Lanzillotta; Sidak Pal Singh; Benjamin F. Grewe; Thomas Hofmann 001 (CoLLAs, 2024)

An Art-Centric Perspective on AI-Based Content Moderation of Nudity. - Piera Riccio; Georgina Curto; Thomas Hofmann 001; Nuria Oliver (ECCV Workshops (5), 2024)

Local and Global Decoding in Text Generation. - Daniel Gareev; Thomas Hofmann 001; Ezhilmathi Krishnasamy; Tiago Pimentel (EMNLP (Findings), 2024)

Simplifying Transformer Blocks. - Bobby He; Thomas Hofmann 001 (ICLR, 2024)

Transformer Fusion with Optimal Transport. - Moritz Imfeld; Jacopo Graldi; Marco Giordano; Thomas Hofmann 001; Sotiris Anagnostidis; Sidak Pal Singh (ICLR, 2024)

Towards Meta-Pruning via Optimal Transport. - Alexander Theus; Olin Geimer; Friedrich Wicke; Thomas Hofmann 001; Sotiris Anagnostidis; Sidak Pal Singh (ICLR, 2024)

Navigating Scaling Laws: Compute Optimality in Adaptive Model Training. - Sotiris Anagnostidis; Gregor Bachmann; Imanol Schlag; Thomas Hofmann 001 (ICML, 2024)

Recurrent Distance Filtering for Graph Representation Learning. - Yuhui Ding; Antonio Orvieto; Bobby He; Thomas Hofmann 001 (ICML, 2024)

A Language Model's Guide Through Latent Space. - Dimitri von Rütte; Sotiris Anagnostidis; Gregor Bachmann; Thomas Hofmann 001 (ICML, 2024)

Understanding and Minimising Outlier Features in Transformer Training. - Bobby He; Lorenzo Noci; Daniele Paliotta; Imanol Schlag; Thomas Hofmann 001 (NeurIPS, 2024)

Super Consistency of Neural Network Landscapes and Learning Rate Transfer. - Lorenzo Noci; Alexandru Meterez; Thomas Hofmann 001; Antonio Orvieto (NeurIPS, 2024)

Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-symbolic Architectures. - Michael Hersche; Francesco Di Stefano; Thomas Hofmann 001; Abu Sebastian; Abbas Rahimi (CoRR, 2024)

Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning. - Lorenzo Noci; Alexandru Meterez; Thomas Hofmann 001; Antonio Orvieto (CoRR, 2024)

Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends. - Sidak Pal Singh; Bobby He; Thomas Hofmann 001; Bernhard Schölkopf (CoRR, 2024)

Language Imbalance Can Boost Cross-lingual Generalisation. - Anton Schäfer; Shauli Ravfogel; Thomas Hofmann 001; Tiago Pimentel; Imanol Schlag (CoRR, 2024)

Object-Attribute Binding in Text-to-Image Generation: Evaluation and Control. - Maria Mihaela Trusca; Wolf Nuyts; Jonathan Thomm; Robert Honig; Thomas Hofmann 001; Tinne Tuytelaars; Marie-Francine Moens (CoRR, 2024)

Understanding and Minimising Outlier Features in Neural Network Training. - Bobby He; Lorenzo Noci; Daniele Paliotta; Imanol Schlag; Thomas Hofmann 001 (CoRR, 2024)

Explicit Word Density Estimation for Language Modelling. - Jovan Andonov; Octavian Ganea; Paulina Grnarova; Gary Bécigneul; Thomas Hofmann 001 (CoRR, 2024)

Landscaping Linear Mode Connectivity. - Sidak Pal Singh; Linara Adilova; Michael Kamp; Asja Fischer; Bernhard Schölkopf; Thomas Hofmann 001 (CoRR, 2024)

PixLens: A Novel Framework for Disentangled Evaluation in Diffusion-Based Image Editing with Object Detection + SAM. - Stefan Stefanache; Lluís Pastor Pérez; Julen Costa Watanabe; Ernesto Sanchez Tejedor; Thomas Hofmann 001; Enis Simsar (CoRR, 2024)

MegaPortrait: Revisiting Diffusion Control for High-fidelity Portrait Generation. - Han Yang; Sotiris Anagnostidis; Enis Simsar; Thomas Hofmann 001 (CoRR, 2024)

UIP2P: Unsupervised Instruction-based Image Editing via Cycle Edit Consistency. - Enis Simsar; Alessio Tonioni; Yongqin Xian; Thomas Hofmann 001; Federico Tombari (CoRR, 2024)

On the Expressiveness and Length Generalization of Selective State Space Models on Regular Languages. - Aleksandar Terzic; Michael Hersche; Giacomo Camposampiero; Thomas Hofmann 001; Abu Sebastian; Abbas Rahimi (AAAI, 2025)

Causal Estimation of Tokenisation Bias. - Pietro Lesci; Clara Meister; Thomas Hofmann 001; Andreas Vlachos 001; Tiago Pimentel (ACL (1), 2025)

Emergence of Globally Attracting Fixed Points in Deep Neural Networks With Nonlinear Activations. - Amir Joudaki; Thomas Hofmann 001 (AISTATS, 2025)

LoRACLR: Contrastive Adaptation for Customization of Diffusion Models. - Enis Simsar; Thomas Hofmann 001; Federico Tombari; Pinar Yanardag (CVPR, 2025)

The Directionality of Optimization Trajectories in Neural Networks. - Sidak Pal Singh; Bobby He; Thomas Hofmann 001; Bernhard Schölkopf (ICLR, 2025)

LIME: Localized Image Editing via Attention Regularization in Diffusion Models. - Enis Simsar; Alessio Tonioni; Yongqin Xian; Thomas Hofmann 001; Federico Tombari (WACV, 2025)

SHYI: Action Support for Contrastive Learning in High-Fidelity Text-to-Image Generation. - Tianxiang Xia; Lin Xiao; Yannick Montorfani; Francesco Pavia; Enis Simsar; Thomas Hofmann 001 (CoRR, 2025)

IC-Portrait: In-Context Matching for View-Consistent Personalized Portrait. - Han Yang; Enis Simsar; Sotiris Anagnostidis; Yanlong Zang; Thomas Hofmann 001; Ziwei Liu (CoRR, 2025)

Generalized Interpolating Discrete Diffusion. - Dimitri von Rütte; Janis Fluri; Yuhui Ding; Antonio Orvieto; Bernhard Schölkopf; Thomas Hofmann 001 (CoRR, 2025)

JEDI: The Force of Jensen-Shannon Divergence in Disentangling Diffusion Models. - Eric Tillmann Bill; Enis Simsar; Thomas Hofmann 001 (CoRR, 2025)

Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment. - Yuhui Ding; Thomas Hofmann 001 (CoRR, 2025)

The Importance of Being Lazy: Scaling Limits of Continual Learning. - Jacopo Graldi; Alessandro Breccia; Giulia Lanzillotta; Thomas Hofmann 001; Lorenzo Noci (CoRR, 2025)

Model Fusion via Neuron Interpolation. - Phoomraphee Luenam; Andreas Spanopoulos; Amit Sant; Thomas Hofmann 001; Sotiris Anagnostidis; Sidak Pal Singh (CoRR, 2025)

The Non-Linear Representation Dilemma: Is Causal Abstraction Enough for Mechanistic Interpretability? - Denis Sutter; Julian Minder; Thomas Hofmann 001; Tiago Pimentel (CoRR, 2025)