Sebastian Nowozin

ORCID

Publication Activity (10 Years)

Years Active: 2007-2023
Publications (10 Years): 76

Top Venues

Berlin Institute of Technology (PHD)

Education History

Berlin Institute of Technology

PHD

Publications

Patrick Anderson, 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, Daniel Cletheroe, Bridgette Cooper, Tim Deegan, Austin Donnelly, Rokas Drevinskas, Alexander L. Gaunt, Christos Gkantsidis, Ariel Gomez Diaz, István Haller, Freddie Hong, Teodora Ilieva, Shashidhar Joshi, Russell Joyce, Mint Kunkel, David Lara, Sergey Legtchenko, Fanglin Linda Liu, Bruno Magalhães, Alana Marzoev, Marvin McNett, Jayashree Mohan, Michael Myrah, Trong Nguyen, Sebastian Nowozin, Aaron Ogus, Hiske Overweg, Antony I. T. Rowstron, Maneesh Sah, Masaaki Sakakura, Peter Scholtz, Nina Schreiner, Omer Sella, Adam Smith, Ioan A. Stefanovici, David Sweeney, Benn Thomsen, Govert Verkes, Phil Wainman, Jonathan Westcott, Luke Weston, Charles Whittaker, Pablo Wilke Berenguer, Hugh Williams, Thomas Winkler, Stefan Winzeck
Project Silica: Towards Sustainable Cloud Archival Storage in Glass. SOSP (2023)
Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. CoRR (2023)
Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E. Turner
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. ICLR (2023)
Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. NeurIPS (2023)
Joowon Lim, Jannes Gladrow, Douglas Kelly, Greg O'Shea, Govert Verkes, Ioan A. Stefanovici, Sebastian Nowozin, Benn Thomsen
High-bandwidth Close-Range Information Transport through Light Pipes. CoRR (2023)
Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E. Turner
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. CoRR (2022)
Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. NeurIPS (2022)
Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. CoRR (2022)
John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
Memory Efficient Meta-Learning with Large Images. CoRR (2021)
Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann
Precise characterization of the prior predictive distribution of deep ReLU networks. CoRR (2021)
Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. CoRR (2021)
Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann
Precise characterization of the prior predictive distribution of deep ReLU networks. NeurIPS (2021)
Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. NeurIPS (2021)
John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard Turner
Memory Efficient Meta-Learning with Large Images. NeurIPS (2021)
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
TaskNorm: Rethinking Batch Normalization for Meta-Learning. CoRR (2020)
Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR (2020)
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR (2020)
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
TaskNorm: Rethinking Batch Normalization for Meta-Learning. ICML (2020)
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML (2020)
Jan Stuehmer, Richard E. Turner, Sebastian Nowozin
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations. AISTATS (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR (2020)
Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner
Meta-Learning Probabilistic Inference for Prediction. ICLR (Poster) (2019)
Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS (2019)
Lars M. Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, Andreas Geiger
Occupancy Networks: Learning 3D Reconstruction in Function Space. CVPR (2019)
Jan Stühmer, Richard E. Turner, Sebastian Nowozin
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations. CoRR (2019)
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR (2019)
Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt
Deterministic Variational Inference for Robust Bayesian Neural Networks. ICLR (2019)
Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model. CoRR (2019)
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. ICML (2019)
James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes. NeurIPS (2019)
James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes. CoRR (2019)
Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. NeurIPS (2019)
Sergey Prokudin, Peter V. Gehler, Sebastian Nowozin
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification. CoRR (2018)
Daniel Coelho de Castro, Sebastian Nowozin
Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model. CoRR (2018)
Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt
Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks. CoRR (2018)
Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann
Adversarially Robust Training through Structured Gradient Regularization. CoRR (2018)
Sergey Prokudin, Peter V. Gehler, Sebastian Nowozin
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification. ECCV (9) (2018)
Lars M. Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, Andreas Geiger
Occupancy Networks: Learning 3D Reconstruction in Function Space. CoRR (2018)
Daniel Coelho de Castro, Sebastian Nowozin
From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data. CoRR (2018)
Lars M. Mescheder, Andreas Geiger, Sebastian Nowozin
Which Training Methods for GANs do actually Converge? ICML (2018)
Sebastian Nowozin
Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference. ICLR (Poster) (2018)
Daniel Coelho de Castro, Sebastian Nowozin
From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data. ECCV (2) (2018)
Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. ICLR (Poster) (2018)
Patrick Anderson, Richard Black, Ausra Cerkauskaite, Andromachi Chatzieleftheriou, James Clegg, Chris Dainty, Raluca Diaconu, Rokas Drevinskas, Austin Donnelly, Alexander L. Gaunt, Andreas Georgiou, Ariel Gomez Diaz, Peter G. Kazansky, David Lara, Sergey Legtchenko, Sebastian Nowozin, Aaron Ogus, Douglas Phillips, Antony I. T. Rowstron, Masaaki Sakakura, Ioan A. Stefanovici, Benn Thomsen, Lei Wang, Hugh Williams, Mengyang Yang
Glass: A New Media for a New Era? HotStorage (2018)
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. CoRR (2018)
Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin
Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations. AAAI (2018)
Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner
Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. CoRR (2018)
Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger
The Numerics of GANs. CoRR (2017)
Sergey Prokudin, Daniel Kappler, Sebastian Nowozin, Peter V. Gehler
Learning to Filter Object Detections. GCPR (2017)
Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. CoRR (2017)
Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe
The Atari Grand Challenge Dataset. CoRR (2017)
Michael Schober, Amit Adam, Omer Yair, Shai Mazor, Sebastian Nowozin
Dynamic Time-of-Flight. CVPR (2017)
Alexander Krull, Eric Brachmann, Sebastian Nowozin, Frank Michel, Jamie Shotton, Carsten Rother
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning. CVPR (2017)
Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann
Stabilizing Training of Generative Adversarial Networks through Regularization. CoRR (2017)
Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger
The Numerics of GANs. NIPS (2017)
Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks. ICML (2017)
Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks. CoRR (2017)
Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations. CoRR (2017)
Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. IEEE Trans. Pattern Anal. Mach. Intell. 39 (5) (2017)
Sergey Tulyakov, Andrew W. Fitzgibbon, Sebastian Nowozin
Hybrid VAE: Improving Deep Generative Models using Partial Observations. CoRR (2017)
Eric Brachmann, Alexander Krull, Sebastian Nowozin, Jamie Shotton, Frank Michel, Stefan Gumhold, Carsten Rother
DSAC - Differentiable RANSAC for Camera Localization. CVPR (2017)
Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann
Stabilizing Training of Generative Adversarial Networks through Regularization. NIPS (2017)
Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
DeepCoder: Learning to Write Programs. ICLR (Poster) (2017)
Diane Bouchacourt, M. Pawan Kumar, Sebastian Nowozin
DISCO Nets: DISsimilarity COefficient Networks. CoRR (2016)
Diane Bouchacourt, Pawan Kumar Mudigonda, Sebastian Nowozin
DISCO Nets : DISsimilarity COefficients Networks. NIPS (2016)
Christian Daniel, Jonathan Taylor, Sebastian Nowozin
Learning Step Size Controllers for Robust Neural Network Training. AAAI (2016)
Olga Ohrimenko, Felix Schuster, Cédric Fournet, Aastha Mehta, Sebastian Nowozin, Kapil Vaswani, Manuel Costa
Oblivious Multi-Party Machine Learning on Trusted Processors. USENIX Security Symposium (2016)
Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger
Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring. CoRR (2016)
Eric Brachmann, Alexander Krull, Sebastian Nowozin, Jamie Shotton, Frank Michel, Stefan Gumhold, Carsten Rother
DSAC - Differentiable RANSAC for Camera Localization. CoRR (2016)
Uwe Schmidt, Jeremy Jancsary, Sebastian Nowozin, Stefan Roth, Carsten Rother
Cascades of Regression Tree Fields for Image Restoration. IEEE Trans. Pattern Anal. Mach. Intell. 38 (4) (2016)
Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
DeepCoder: Learning to Write Programs. CoRR (2016)
Alexander Krull, Eric Brachmann, Sebastian Nowozin, Frank Michel, Jamie Shotton, Carsten Rother
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning. CoRR (2016)
Christoph Dann, Katja Hofmann, Sebastian Nowozin
Memory Lens: How Much Memory Does an Agent Use? CoRR (2016)
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. NIPS (2016)
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. CoRR (2016)
Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. CoRR (2015)
Varun Jampani, Sebastian Nowozin, Matthew Loper, Peter V. Gehler
The informed sampler: A discriminative approach to Bayesian inference in generative computer vision models. Comput. Vis. Image Underst. 136 (2015)
Diane Bouchacourt, Sebastian Nowozin, M. Pawan Kumar
Entropy-Based Latent Structured Output Prediction. ICCV (2015)
Kevin Schelten, Sebastian Nowozin, Jeremy Jancsary, Carsten Rother, Stefan Roth
Interleaved Regression Tree Field Cascades for Blind Image Deconvolution. WACV (2015)
Jan Stühmer, Sebastian Nowozin, Andrew W. Fitzgibbon, Richard Szeliski, Travis Perry, Sunil Acharya, Daniel Cremers, Jamie Shotton
Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations. ICCV (2015)
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, Carsten Rother
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int. J. Comput. Vis. 115 (2) (2015)
Varun Jampani, Sebastian Nowozin, Matthew Loper, Peter V. Gehler
The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models. CoRR (2014)
Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. ICML (2014)
Daniel Khashabi, Sebastian Nowozin, Jeremy Jancsary, Andrew W. Fitzgibbon
Joint Demosaicing and Denoising via Learned Nonparametric Random Fields. IEEE Trans. Image Process. 23 (12) (2014)
Sebastian Nowozin
Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case. CVPR (2014)
Sungwoong Kim, Chang Dong Yoo, Sebastian Nowozin, Pushmeet Kohli
Image Segmentation UsingHigher-Order Correlation Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 36 (9) (2014)
Yuting Wu, Daniel J. Holland, Mick D. Mantle, Andrew Gordon Wilson, Sebastian Nowozin, Andrew Blake, Lynn F. Gladden
A Bayesian method to quantifying chemical composition using NMR: Application to porous media systems. EUSIPCO (2014)
Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin
Efficient Nonlinear Markov Models for Human Motion. CVPR (2014)
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, Carsten Rother
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR (2014)
Uwe Schmidt, Jeremy Jancsary, Sebastian Nowozin, Stefan Roth, Carsten Rother
Cascades of Regression Tree Fields for Image Restoration. CoRR (2014)
Uwe Schmidt, Carsten Rother, Sebastian Nowozin, Jeremy Jancsary, Stefan Roth
Discriminative Non-blind Deblurring. CVPR (2013)
Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin
A Non-parametric Bayesian Network Prior of Human Pose. ICCV (2013)
Po-Ling Loh, Sebastian Nowozin
Faster Hoeffding Racing: Bernstein Races via Jackknife Estimates. ALT (2013)
Jeremy Jancsary, Sebastian Nowozin, Carsten Rother
Learning Convex QP Relaxations for Structured Prediction. ICML (3) (2013)
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
A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. CVPR (2013)
Jamie Shotton, Toby Sharp, Pushmeet Kohli, Sebastian Nowozin, John M. Winn, Antonio Criminisi
Decision Jungles: Compact and Rich Models for Classification. NIPS (2013)
Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, Chang D. Yoo
Task-Specific Image Partitioning. IEEE Trans. Image Process. 22 (2) (2013)
Sebastian Nowozin
Improved Information Gain Estimates for Decision Tree Induction. ICML (2012)
Jeremy Jancsary, Sebastian Nowozin, Toby Sharp, Carsten Rother
Regression Tree Fields - An efficient, non-parametric approach to image labeling problems. CVPR (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sebastian Nowozin