Sebastian Nowozin

Orcid: 0000-0003-0347-0852

According to our database1, Sebastian Nowozin authored at least 94 papers between 2007 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
High-bandwidth Close-Range Information Transport through Light Pipes.
CoRR, 2023


Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Precise characterization of the prior predictive distribution of deep ReLU networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Memory Efficient Meta-Learning with Large Images.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Hydra: Preserving Ensemble Diversity for Model Distillation.
CoRR, 2020

How Good is the Bayes Posterior in Deep Neural Networks Really?
Proceedings of the 37th International Conference on Machine Learning, 2020

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

TaskNorm: Rethinking Batch Normalization for Meta-Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model.
CoRR, 2019

Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE.
Proceedings of the 36th International Conference on Machine Learning, 2019

Deterministic Variational Inference for Robust Bayesian Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Meta-Learning Probabilistic Inference for Prediction.
Proceedings of the 7th International Conference on Learning Representations, 2019

Occupancy Networks: Learning 3D Reconstruction in Function Space.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model.
CoRR, 2018

Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks.
CoRR, 2018

Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning.
CoRR, 2018

Adversarially Robust Training through Structured Gradient Regularization.
CoRR, 2018

Which Training Methods for GANs do actually Converge?
Proceedings of the 35th International Conference on Machine Learning, 2018

PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference.
Proceedings of the 6th International Conference on Learning Representations, 2018


Deep Directional Statistics: Pose Estimation with Uncertainty Quantification.
Proceedings of the Computer Vision - ECCV 2018, 2018

From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data.
Proceedings of the Computer Vision - ECCV 2018, 2018

Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

Hybrid VAE: Improving Deep Generative Models using Partial Observations.
CoRR, 2017

The Atari Grand Challenge Dataset.
CoRR, 2017

Stabilizing Training of Generative Adversarial Networks through Regularization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Numerics of GANs.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

DeepCoder: Learning to Write Programs.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to Filter Object Detections.
Proceedings of the Pattern Recognition - 39th German Conference, 2017

Dynamic Time-of-Flight.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

DSAC - Differentiable RANSAC for Camera Localization.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Cascades of Regression Tree Fields for Image Restoration.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring.
CoRR, 2016

Memory Lens: How Much Memory Does an Agent Use?
CoRR, 2016

DISCO Nets: DISsimilarity COefficient Networks.
CoRR, 2016

Oblivious Multi-Party Machine Learning on Trusted Processors.
Proceedings of the 25th USENIX Security Symposium, 2016

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

DISCO Nets : DISsimilarity COefficients Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Step Size Controllers for Robust Neural Network Training.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
Int. J. Comput. Vis., 2015

The informed sampler: A discriminative approach to Bayesian inference in generative computer vision models.
Comput. Vis. Image Underst., 2015

Interleaved Regression Tree Field Cascades for Blind Image Deconvolution.
Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision, 2015

Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Entropy-Based Latent Structured Output Prediction.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
Joint Demosaicing and Denoising via Learned Nonparametric Random Fields.
IEEE Trans. Image Process., 2014

Image Segmentation UsingHigher-Order Correlation Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications.
Proceedings of the 31th International Conference on Machine Learning, 2014

A Bayesian method to quantifying chemical composition using NMR: Application to porous media systems.
Proceedings of the 22nd European Signal Processing Conference, 2014

Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Efficient Nonlinear Markov Models for Human Motion.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Task-Specific Image Partitioning.
IEEE Trans. Image Process., 2013

Decision Jungles: Compact and Rich Models for Classification.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Learning Convex QP Relaxations for Structured Prediction.
Proceedings of the 30th International Conference on Machine Learning, 2013

A Non-parametric Bayesian Network Prior of Human Pose.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Discriminative Non-blind Deblurring.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Faster Hoeffding Racing: Bernstein Races via Jackknife Estimates.
Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

2012
Improved Information Gain Estimates for Decision Tree Induction.
Proceedings of the 29th International Conference on Machine Learning, 2012

Loss-Specific Training of Non-Parametric Image Restoration Models: A New State of the Art.
Proceedings of the Computer Vision - ECCV 2012, 2012

Information Theoretic Clustering Using Minimum Spanning Trees.
Proceedings of the Pattern Recognition, 2012

Pottics - The Potts Topic Model for Semantic Image Segmentation.
Proceedings of the Pattern Recognition, 2012

Regression Tree Fields - An efficient, non-parametric approach to image labeling problems.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Instructing people for training gestural interactive systems.
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2012

2011
Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Structured Learning and Prediction in Computer Vision.
Found. Trends Comput. Graph. Vis., 2011

Higher-Order Correlation Clustering for Image Segmentation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Decision tree fields.
Proceedings of the IEEE International Conference on Computer Vision, 2011

Putting MAP Back on the Map.
Proceedings of the Pattern Recognition - 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31, 2011

Variable grouping for energy minimization.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness.
SIAM J. Imaging Sci., 2010

On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation.
Proceedings of the Computer Vision - ECCV 2010, 2010

2009
Learning with structured data: applications to computer vision.
PhD thesis, 2009

gBoost: a mathematical programming approach to graph classification and regression.
Mach. Learn., 2009

Solution stability in linear programming relaxations: graph partitioning and unsupervised learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

On feature combination for multiclass object classification.
Proceedings of the IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27, 2009

Global connectivity potentials for random field models.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

Let the kernel figure it out; Principled learning of pre-processing for kernel classifiers.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

Combining appearance and motion for human action classification in videos.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009

2008
A decoupled approach to exemplar-based unsupervised learning.
Proceedings of the Machine Learning, 2008

Frequent Subgraph Retrieval in Geometric Graph Databases.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
Discriminative Subsequence Mining for Action Classification.
Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

Weighted Substructure Mining for Image Analysis.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007


  Loading...