Josip Djolonga

Papers

• Representation learning from videos in-the-wild: An object-centric approach
  Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
  Winter Conference on Applications of Computer Vision (WACV), 2021
  

• Fast Differentiable Ranking and Sorting
  Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
  International Conference on Machine Learning (ICML), 2020
  

• Self-Supervised Learning of Video-Induced Visual Invariances
  Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Xiaohua Zhai, Neil Houlsby, Sylvain Gelly, Mario Lucic
  Conference on Computer Vision and Pattern Recognition (CVPR), 2020
  

• You Only Train Once: Loss-Conditional Training of Deep Networks
  Alexey Dosovitskiy, Josip Djolonga
  International Conference on Learning Representations (ICLR), 2020
  

• On Mutual Information Maximization for Representation Learning
  Michael Tschannen^*, Josip Djolonga^*, Paul K Rubenstein, Sylvain Gelly, Mario Lucic, ^*=equal contribution
  International Conference on Learning Representations (ICLR), 2020
  

• Precision-Recall Curves Using Information Divergence Frontiers
  Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
  

• A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
  Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, Andre Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby
  arXiv preprint arXiv:1910.04867
  

• Practical and Consistent Estimation of f-Divergences
  Paul K Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya Tolstikhin
  Neural Information Processing Systems (NeurIPS), 2019
  

• Provable Variational Inference for Constrained Log-Submodular Models
  Josip Djolonga, Stefanie Jegelka, Andreas Krause
  Neural Information Processing Systems (NeurIPS), 2018

  @inproceedings{djolonga18provable,
    author = {Djolonga, Josip and Jegelka, Stefanie and Krause, Andreas},
    booktitle = {Neural Information Processing Systems (NeurIPS)},
    title = {Provable Variational Inference for Constrained Log-Submodular Models},
    year = {2018}}
  

  
  

• Learning Implicit Generative Models Using Differentiable Graph Tests
  Josip Djolonga, Andreas Krause
  arXiv preprint arXiv1709.01006 (2017)

  @article{djolonga17graphtests,
    author = {Djolonga, Josip and Krause, Andreas},
    title = Learning Implicit Generative Models Using Differentiable Graph Tests,
    journal = {ArXiv e-prints},
    archivePrefix = "arXiv",
    eprint = {1709.01006},
    primaryClass = "stat.ML",
    year = 2017,
    month = sep}
  

  
  

• Differentiable Learning of Submodular Models
  Josip Djolonga, Andreas Krause
  Neural Information Processing Systems (NIPS), 2017 (spotlight)

  @inproceedings{djolonga17learning,
    author = {Djolonga, Josip and Krause, Andreas},
    booktitle = {Neural Information Processing Systems (NIPS)},
    title = {Differentiable Learning of Submodular Models},
    year = {2017}}
  

  
  

• Improving Optimization-Based Approximate Inference by Clamping Variables
  Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
  Conference on Uncertainty in Artificial Intelligence (UAI), 2017 (oral presentation)

  @inproceedings{zhao17clamping,
    author = {Zhao, Junyao and Djolonga, Josip and Tschiatschek, Sebastian  and Krause, Andreas},
    booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
    title = {Improving Optimization-Based Approximate Inference by Clamping Variables},
    year = {2017}}
  

  
  

• Cooperative Graphical Models
  Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause
  Neural Information Processing Systems (NIPS), 2016

  @inproceedings{djolonga16cooperative,
    author = {Djolonga, Josip and Jegelka, Stefanie and Tschiatschek, Sebastian and Krause, Andreas},
    booktitle = {Neural Information Processing Systems (NIPS)},
    title = {Cooperative Graphical Models},
    year = {2016}}
  

  
  

• Variational Inference in Mixed Probabilistic Submodular Models
  Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
  Neural Information Processing Systems (NIPS), 2016

  @inproceedings{djolonga16mixed,
    author = {Djolonga, Josip and Tschiatschek, Sebastian and Krause, Andreas},
    booktitle = {Neural Information Processing Systems (NIPS)},
    title = {Variational Inference in Mixed Probabilistic Submodular Models},
    year = {2016}}
  

  
  

• Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation,
  Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
  International Conference on Artificial Intelligence and Statistics (AISTATS) 2016

  @inproceedings{tschiatschek16diversity,
    author = {Tschiatschek, Sebastian and Djolonga, Josip and Krause, Andreas},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    title = {Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation},
    year = {2016}}
  

  
  

• Higher-Order Inference for Multi-class Log-supermodular Models
  Jian Zhang, Josip Djolonga, Andreas Krause
  International Conference on Computer Vision (ICCV), 2015

  @inproceedings{zhang15multiclass,
    author = {Zhang, Jian and Djolonga, Josip and Krause, Andreas},
    booktitle = {International Conference on Computer Vision (ICCV)},
    title = {Higher-Order Inference for Multi-class Log-supermodular Models},
    year = {2015}}
  

  
  

• Scalable Variational Inference in Log-supermodular Models
  Josip Djolonga, Andreas Krause
  International Conference on Machine Learning (ICML), 2015

  @inproceedings{djolonga15scalable,
    author = {Djolonga, Josip and Krause, Andreas},
    booktitle = {International Conference on Machine Learning (ICML)},
    title = {Scalable Variational Inference in Log-supermodular Models},
    year = {2015}}
  

  
  

• From MAP to Marginals: Variational Inference in Bayesian Submodular Models
  Josip Djolonga, Andreas Krause
  Neural Information Processing Systems (NIPS), 2014 ◦ code

  @inproceedings{djolonga14variational,
    author = {Djolonga, Josip and Krause, Andreas},
    booktitle = {Neural Information Processing Systems (NIPS)},
    title = {From MAP to Marginals: Variational Inference in Bayesian Submodular Models},
    year = {2014}}
  

  
  

• High-Dimensional Gaussian Process Bandits
  Josip Djolonga, Andreas Krause, Volkan Cevher
  Neural Information Processing Systems (NIPS), 2013

  @inproceedings{djolonga13high,
    author = {Djolonga, Josip and Krause, Andreas and Cevher, Volkan},
    booktitle = {Neural Information Processing Systems (NIPS)},
    title = {High-Dimensional Gaussian Process Bandits},
    year = {2013}}