Weighted Substructure Mining for Image Analysis. - Sebastian Nowozin; Koji Tsuda; Takeaki Uno; Taku Kudo; Gökhan H. Bakir (CVPR, 2007)

Discriminative Subsequence Mining for Action Classification. - Sebastian Nowozin; Gökhan H. Bakir; Koji Tsuda (ICCV, 2007)

Frequent Subgraph Retrieval in Geometric Graph Databases. - Sebastian Nowozin; Koji Tsuda (ICDM, 2008)

A decoupled approach to exemplar-based unsupervised learning. - Sebastian Nowozin; Gökhan H. Bakir (ICML, 2008)

Combining appearance and motion for human action classification in videos. - Paramveer S. Dhillon; Sebastian Nowozin; Christoph H. Lampert (CVPR Workshops, 2009)

Let the kernel figure it out; Principled learning of pre-processing for kernel classifiers. - Peter V. Gehler; Sebastian Nowozin (CVPR, 2009)

Global connectivity potentials for random field models. - Sebastian Nowozin; Christoph H. Lampert (CVPR, 2009)

On feature combination for multiclass object classification. - Peter V. Gehler; Sebastian Nowozin (ICCV, 2009)

Solution stability in linear programming relaxations: graph partitioning and unsupervised learning. - Sebastian Nowozin; Stefanie Jegelka (ICML, 2009)

gBoost: a mathematical programming approach to graph classification and regression. - Hiroto Saigo; Sebastian Nowozin; Tadashi Kadowaki; Taku Kudo; Koji Tsuda (Mach. Learn., 2009)

Learning with structured data: applications to computer vision. - Sebastian Nowozin (2009)

On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation. - Sebastian Nowozin; Peter V. Gehler; Christoph H. Lampert (ECCV (6), 2010)

Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness. - Sebastian Nowozin; Christoph H. Lampert (SIAM J. Imaging Sci., 2010)

Variable grouping for energy minimization. - Taesup Kim; Sebastian Nowozin; Pushmeet Kohli; Chang D. Yoo (CVPR, 2011)

Putting MAP Back on the Map. - Patrick Pletscher; Sebastian Nowozin; Pushmeet Kohli; Carsten Rother (DAGM-Symposium, 2011)

Decision tree fields. - Sebastian Nowozin; Carsten Rother; Shai Bagon; Toby Sharp; Bangpeng Yao; Pushmeet Kohli (ICCV, 2011)

Higher-Order Correlation Clustering for Image Segmentation. - Sungwoong Kim; Sebastian Nowozin; Pushmeet Kohli; Chang Dong Yoo (NIPS, 2011)

Structured Learning and Prediction in Computer Vision. - Sebastian Nowozin; Christoph H. Lampert (Found. Trends Comput. Graph. Vis., 2011)

Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm. - Dhruv Batra; Sebastian Nowozin; Pushmeet Kohli (AISTATS, 2011)

Instructing people for training gestural interactive systems. - Simon Fothergill; Helena M. Mentis; Pushmeet Kohli; Sebastian Nowozin (CHI, 2012)

Regression Tree Fields - An efficient, non-parametric approach to image labeling problems. - Jeremy Jancsary; Sebastian Nowozin; Toby Sharp; Carsten Rother (CVPR, 2012)

Pottics - The Potts Topic Model for Semantic Image Segmentation. - Christoph Dann; Peter V. Gehler; Stefan Roth 001; Sebastian Nowozin (DAGM/OAGM Symposium, 2012)

Information Theoretic Clustering Using Minimum Spanning Trees. - Andreas C. Müller 001; Sebastian Nowozin; Christoph H. Lampert (DAGM/OAGM Symposium, 2012)

Loss-Specific Training of Non-Parametric Image Restoration Models: A New State of the Art. - Jeremy Jancsary; Sebastian Nowozin; Carsten Rother (ECCV (7), 2012)

Improved Information Gain Estimates for Decision Tree Induction. - Sebastian Nowozin (ICML, 2012)

Faster Hoeffding Racing: Bernstein Races via Jackknife Estimates. - Po-Ling Loh; Sebastian Nowozin (ALT, 2013)

A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. - Jörg H. Kappes; Björn Andres; Fred A. Hamprecht; Christoph Schnörr; Sebastian Nowozin; Dhruv Batra; Sungwoong Kim; Bernhard X. Kausler; Jan Lellmann; Nikos Komodakis; Carsten Rother (CVPR, 2013)

Discriminative Non-blind Deblurring. - Uwe Schmidt 001; Carsten Rother; Sebastian Nowozin; Jeremy Jancsary; Stefan Roth 001 (CVPR, 2013)

A Non-parametric Bayesian Network Prior of Human Pose. - Andreas M. Lehrmann; Peter V. Gehler; Sebastian Nowozin (ICCV, 2013)

Learning Convex QP Relaxations for Structured Prediction. - Jeremy Jancsary; Sebastian Nowozin; Carsten Rother (ICML (3), 2013)

Decision Jungles: Compact and Rich Models for Classification. - Jamie Shotton; Toby Sharp; Pushmeet Kohli; Sebastian Nowozin; John M. Winn; Antonio Criminisi (NIPS, 2013)

Task-Specific Image Partitioning. - Sungwoong Kim; Sebastian Nowozin; Pushmeet Kohli; Chang D. Yoo (IEEE Trans. Image Process., 2013)

Efficient Nonlinear Markov Models for Human Motion. - Andreas M. Lehrmann; Peter V. Gehler; Sebastian Nowozin (CVPR, 2014)

Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case. - Sebastian Nowozin (CVPR, 2014)

A Bayesian method to quantifying chemical composition using NMR: Application to porous media systems. - Yuting Wu; Daniel J. Holland; Mick D. Mantle; Andrew Gordon Wilson; Sebastian Nowozin; Andrew Blake 001; Lynn F. Gladden (EUSIPCO, 2014)

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. - Sébastien Bratières; Novi Quadrianto; Sebastian Nowozin; Zoubin Ghahramani (ICML, 2014)

Image Segmentation UsingHigher-Order Correlation Clustering. - Sungwoong Kim; Chang Dong Yoo; Sebastian Nowozin; Pushmeet Kohli (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Joint Demosaicing and Denoising via Learned Nonparametric Random Fields. - Daniel Khashabi; Sebastian Nowozin; Jeremy Jancsary; Andrew W. Fitzgibbon (IEEE Trans. Image Process., 2014)

Entropy-Based Latent Structured Output Prediction. - Diane Bouchacourt; Sebastian Nowozin; M. Pawan Kumar (ICCV, 2015)

Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations. - Jan Stühmer; Sebastian Nowozin; Andrew W. Fitzgibbon; Richard Szeliski; Travis Perry; Sunil Acharya; Daniel Cremers; Jamie Shotton (ICCV, 2015)

Interleaved Regression Tree Field Cascades for Blind Image Deconvolution. - Kevin Schelten; Sebastian Nowozin; Jeremy Jancsary; Carsten Rother; Stefan Roth 001 (WACV, 2015)

The informed sampler: A discriminative approach to Bayesian inference in generative computer vision models. - Varun Jampani; Sebastian Nowozin; Matthew Loper; Peter V. Gehler (Comput. Vis. Image Underst., 2015)

A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. - Jörg H. Kappes; Björn Andres; Fred A. Hamprecht; Christoph Schnörr; Sebastian Nowozin; Dhruv Batra; Sungwoong Kim; Bernhard X. Kausler; Thorben Kröger; Jan Lellmann; Nikos Komodakis; Bogdan Savchynskyy; et al. (Int. J. Comput. Vis., 2015)

Learning Step Size Controllers for Robust Neural Network Training. - Christian Daniel; Jonathan Taylor; Sebastian Nowozin (AAAI, 2016)

DISCO Nets : DISsimilarity COefficients Networks. - Diane Bouchacourt; Pawan Kumar Mudigonda; Sebastian Nowozin (NIPS, 2016)

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. - Sebastian Nowozin; Botond Cseke; Ryota Tomioka (NIPS, 2016)

Oblivious Multi-Party Machine Learning on Trusted Processors. - Olga Ohrimenko; Felix Schuster; Cédric Fournet; Aastha Mehta; Sebastian Nowozin; Kapil Vaswani; Manuel Costa (USENIX Security Symposium, 2016)

DISCO Nets: DISsimilarity COefficient Networks. - Diane Bouchacourt; M. Pawan Kumar; Sebastian Nowozin (CoRR, 2016)

Memory Lens: How Much Memory Does an Agent Use? - Christoph Dann; Katja Hofmann; Sebastian Nowozin (CoRR, 2016)

Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring. - Lars M. Mescheder; Sebastian Nowozin; Andreas Geiger 001 (CoRR, 2016)

Cascades of Regression Tree Fields for Image Restoration. - Uwe Schmidt 001; Jeremy Jancsary; Sebastian Nowozin; Stefan Roth 001; Carsten Rother (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

DSAC - Differentiable RANSAC for Camera Localization. - Eric Brachmann; Alexander Krull; Sebastian Nowozin; Jamie Shotton; Frank Michel 002; Stefan Gumhold; Carsten Rother (CVPR, 2017)

PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning. - Alexander Krull; Eric Brachmann; Sebastian Nowozin; Frank Michel 002; Jamie Shotton; Carsten Rother (CVPR, 2017)

Dynamic Time-of-Flight. - Michael Schober; Amit Adam; Omer Yair; Shai Mazor; Sebastian Nowozin (CVPR, 2017)

Learning to Filter Object Detections. - Sergey Prokudin; Daniel Kappler; Sebastian Nowozin; Peter V. Gehler (GCPR, 2017)

DeepCoder: Learning to Write Programs. - Matej Balog; Alexander L. Gaunt; Marc Brockschmidt; Sebastian Nowozin; Daniel Tarlow (ICLR (Poster), 2017)

Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks. - Lars M. Mescheder; Sebastian Nowozin; Andreas Geiger 001 (ICML, 2017)

The Numerics of GANs. - Lars M. Mescheder; Sebastian Nowozin; Andreas Geiger 001 (NIPS, 2017)

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

The Atari Grand Challenge Dataset. - Vitaly Kurin; Sebastian Nowozin; Katja Hofmann; Lucas Beyer; Bastian Leibe (CoRR, 2017)

Hybrid VAE: Improving Deep Generative Models using Partial Observations. - Sergey Tulyakov; Andrew W. Fitzgibbon; Sebastian Nowozin (CoRR, 2017)

Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. - Amit Adam; Christoph Dann; Omer Yair; Shai Mazor; Sebastian Nowozin (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations. - Diane Bouchacourt; Ryota Tomioka; Sebastian Nowozin (AAAI, 2018)

From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data. - Daniel Coelho de Castro; Sebastian Nowozin (ECCV (2), 2018)

Deep Directional Statistics: Pose Estimation with Uncertainty Quantification. - Sergey Prokudin; Peter V. Gehler; Sebastian Nowozin (ECCV (9), 2018)

Glass: A New Media for a New Era? - Patrick Anderson 001; Richard Black; Ausra Cerkauskaite; Andromachi Chatzieleftheriou; James Clegg; Chris Dainty; Raluca Diaconu; Rokas Drevinskas; Austin Donnelly; Alexander L. Gaunt; Andreas Georgiou; Ariel Gomez Diaz; et al. (HotStorage, 2018)

Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference. - Sebastian Nowozin (ICLR (Poster), 2018)

PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. - Yang Song 011; Taesup Kim; Sebastian Nowozin; Stefano Ermon; Nate Kushman (ICLR (Poster), 2018)

Which Training Methods for GANs do actually Converge? - Lars M. Mescheder; Andreas Geiger 001; Sebastian Nowozin (ICML, 2018)

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

Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. - Jonathan Gordon 003; John Bronskill; Matthias Bauer 001; Sebastian Nowozin; Richard E. Turner (CoRR, 2018)

Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks. - Anqi Wu; Sebastian Nowozin; Edward Meeds; Richard E. Turner; José Miguel Hernández-Lobato; Alexander L. Gaunt (CoRR, 2018)

Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model. - Daniel Coelho de Castro; Sebastian Nowozin (CoRR, 2018)

Occupancy Networks: Learning 3D Reconstruction in Function Space. - Lars M. Mescheder; Michael Oechsle; Michael Niemeyer; Sebastian Nowozin; Andreas Geiger 001 (CVPR, 2019)

Meta-Learning Probabilistic Inference for Prediction. - Jonathan Gordon 003; John Bronskill; Matthias Bauer 001; Sebastian Nowozin; Richard E. Turner (ICLR (Poster), 2019)

Deterministic Variational Inference for Robust Bayesian Neural Networks. - Anqi Wu; Sebastian Nowozin; Edward Meeds; Richard E. Turner; José Miguel Hernández-Lobato; Alexander L. Gaunt (ICLR, 2019)

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. - Chao Ma 019; Sebastian Tschiatschek; Konstantina Palla; José Miguel Hernández-Lobato; Sebastian Nowozin; Cheng Zhang 005 (ICML, 2019)

Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. - Wenbo Gong 001; Sebastian Tschiatschek; Sebastian Nowozin; Richard E. Turner; José Miguel Hernández-Lobato; Cheng Zhang 005 (NeurIPS, 2019)

Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes. - James Requeima; Jonathan Gordon 003; John Bronskill; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2019)

Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. - Jasper Snoek; Yaniv Ovadia; Emily Fertig; Balaji Lakshminarayanan; Sebastian Nowozin; D. Sculley; Joshua V. Dillon; Jie Ren 006; Zachary Nado (NeurIPS, 2019)

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model. - Wenbo Gong 001; Sebastian Tschiatschek; Richard E. Turner; Sebastian Nowozin; José Miguel Hernández-Lobato; Cheng Zhang 005 (CoRR, 2019)

Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations. - Jan Stuehmer; Richard E. Turner; Sebastian Nowozin (AISTATS, 2020)

TaskNorm: Rethinking Batch Normalization for Meta-Learning. - John Bronskill; Jonathan Gordon 003; James Requeima; Sebastian Nowozin; Richard E. Turner (ICML, 2020)

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. - Jakub Swiatkowski; Kevin Roth; Bastiaan S. Veeling; Linh Tran; Joshua V. Dillon; Jasper Snoek; Stephan Mandt; Tim Salimans; Rodolphe Jenatton; Sebastian Nowozin (ICML, 2020)

How Good is the Bayes Posterior in Deep Neural Networks Really? - Florian Wenzel; Kevin Roth; Bastiaan S. Veeling; Jakub Swiatkowski; Linh Tran; Stephan Mandt; Jasper Snoek; Tim Salimans; Rodolphe Jenatton; Sebastian Nowozin (ICML, 2020)

Hydra: Preserving Ensemble Diversity for Model Distillation. - Linh Tran; Bastiaan S. Veeling; Kevin Roth; Jakub Swiatkowski; Joshua V. Dillon; Jasper Snoek; Stephan Mandt; Tim Salimans; Sebastian Nowozin; Rodolphe Jenatton (CoRR, 2020)

Memory Efficient Meta-Learning with Large Images. - John Bronskill; Daniela Massiceti; Massimiliano Patacchiola; Katja Hofmann; Sebastian Nowozin; Richard E. Turner (NeurIPS, 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)

Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. - Massimiliano Patacchiola; John Bronskill; Aliaksandra Shysheya; Katja Hofmann; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2022)

FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. - Aliaksandra Shysheya; John Bronskill; Massimiliano Patacchiola; Sebastian Nowozin; Richard E. Turner (ICLR, 2023)

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. - Leon Klein; Andrew Y. K. Foong; Tor Erlend Fjelde; Bruno Mlodozeniec; Marc Brockschmidt; Sebastian Nowozin; Frank Noé; Ryota Tomioka (NeurIPS, 2023)

Project Silica: Towards Sustainable Cloud Archival Storage in Glass. - Patrick Anderson 001; Erika Blancada Aranas; Youssef Assaf; Raphael Behrendt; Richard Black; Marco Caballero; Pashmina Cameron; Burcu Canakci; Thales De Carvalho; Andromachi Chatzieleftheriou; Rebekah Storan Clarke; James Clegg; et al. (SOSP, 2023)

High-bandwidth Close-Range Information Transport through Light Pipes. - Joowon Lim; Jannes Gladrow; Douglas J. Kelly; Greg O'Shea; Govert Verkes; Ioan A. Stefanovici; Sebastian Nowozin; Benn Thomsen (CoRR, 2023)

Project Silica: Towards Sustainable Cloud Archival Storage in Glass. - Patrick Anderson 001; Erika Blancada Aranas; Youssef Assaf; Raphael Behrendt; Richard Black; Marco Caballero; Pashmina Cameron; Burcu Canakci; Andromachi Chatzieleftheriou; Rebekah Storan Clarke; James Clegg; Daniel Cletheroe; et al. (ACM Trans. Storage, 2025)

AlphaEvolve: A coding agent for scientific and algorithmic discovery. - Alexander Novikov 001; Ngân Vu; Marvin Eisenberger; Emilien Dupont; Po-Sen Huang; Adam Zsolt Wagner; Sergey Shirobokov; Borislav Kozlovskii; Francisco J. R. Ruiz; Abbas Mehrabian; M. Pawan Kumar; Abigail See; et al. (CoRR, 2025)