@unpublished{Aczel2025a,
  author = "T. Aczel and L. Theis and R. Wattenhofer",
  title = "Efficient Bayesian Inference from Noisy Pairwise Comparisons",
  year = 2025,
  url = "https://arxiv.org/abs/2510.09333v1",
  note = "arXiv:2510.09333"
}


@inproceedings{Kobus2024a,
  author = "S. Kobus and L. Theis and D. Gündüz",
  title = "Gaussian Channel Simulation with Rotated Dithered Quantization",
  year = 2024,
  booktitle = "IEEE International Symposium on Information Theory",
  url = "https://arxiv.org/abs/2407.12970"
}


@inproceedings{Theis2024a,
  author = "L. Theis",
  title = "What makes an image realistic?",
  year = 2024,
  booktitle = "Proceedings of the 41st International Conference on Machine Learning",
  keywords = "perceptual quality, realism, compression, generative modeling, outlier detection",
  url = "https://arxiv.org/abs/2403.04493"
}


@inproceedings{Kim2023a,
  author = "H. Kim and M. Bauer and L. Theis and J. R. Schwarz and E. Dupont",
  title = "C3: High-performance and low-complexity neural compression from a single image or video",
  year = 2024,
  booktitle = "Computer Vision and Pattern Recognition",
  keywords = "compression",
  url = "https://arxiv.org/abs/2312.02753"
}


@inproceedings{Severo2023a,
  author = "D. Severo and L. Theis and J. Ballé",
  title = "The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric",
  year = 2024,
  booktitle = "International Conference on Learning Representations",
  keywords = "perceptual quality, bapps, lpips, lasi, ssim",
  url = "https://arxiv.org/abs/2310.05986"
}


@unpublished{Hoogeboom2023a,
  author = "E. Hoogeboom and E. Agustsson and F. Mentzer and L. Versari and G. Toderici and L. Theis",
  title = "High-Fidelity Image Compression with Score-based Generative Models",
  year = 2023,
  keywords = "compression, diffusion, rectified flow",
  url = "https://arxiv.org/abs/2305.18231",
  note = "arXiv:2305.18231"
}


@inproceedings{Flamich2023a,
  author = "G. Flamich and L. Theis",
  title = "Adaptive Greedy Rejection Sampling",
  year = 2023,
  booktitle = "IEEE International Symposium on Information Theory",
  keywords = "channel simulation, compression, information theory",
  url = "https://arxiv.org/abs/2304.10407"
}


@article{Yang2023a,
  author = "Y. Yang and S. Mandt and L. Theis",
  title = "An Introduction to Neural Data Compression",
  year = 2023,
  journal = "Foundations and Trends in Computer Graphics and Vision",
  volume = 15,
  number = 2,
  pages = "113-200",
  keywords = "compression",
  url = "http://dx.doi.org/10.1561/0600000107"
}


@unpublished{Theis2022b,
  author = "L. Theis and T. Salimans and M. D. Hoffman and F. Mentzer",
  title = "Lossy Compression with Gaussian Diffusion",
  year = 2022,
  keywords = "compression, diffusion, channel simulation",
  url = "https://arxiv.org/abs/2206.08889",
  note = "arXiv:2206.08889"
}


@inproceedings{Shah2021a,
  author = "A. Shah and W.-N. Chen and J. Balle and P. Kairouz and L. Theis",
  title = "Optimal Compression of Locally Differentially Private Mechanisms",
  year = 2022,
  booktitle = "Artificial Intelligence and Statistics",
  keywords = "differential privacy, compression, channel simulation",
  url = "https://arxiv.org/abs/2111.00092"
}


@inproceedings{theis2022algorithms,
  author = "L. Theis and N. Yosri",
  title = "Algorithms for the Communication of Samples",
  year = 2022,
  booktitle = "Proceedings of the 39th International Conference on Machine Learning",
  keywords = "compression, information theory, channel simulation",
  url = "https://arxiv.org/abs/2110.12805"
}


@inproceedings{Theis2021c,
  author = "L. Theis and J. Ho",
  title = "Importance weighted compression",
  year = 2021,
  booktitle = "Neural Compression Workshop at ICLR",
  keywords = "compression, deep learning, bits back",
  url = "https://openreview.net/forum?id=n6skss_9-v3"
}


@inproceedings{Theis2021b,
  author = "L. Theis and A. B. Wagner",
  title = "A coding theorem for the rate-distortion-perception function",
  year = 2021,
  booktitle = "Neural Compression Workshop at ICLR",
  keywords = "compression, information theory, perceptual quality",
  url = "https://arxiv.org/abs/2104.13662"
}


@inproceedings{Theis2021a,
  author = "L. Theis and E. Agustsson",
  title = "On the advantages of stochastic encoders",
  year = 2021,
  booktitle = "Neural Compression Workshop at ICLR",
  keywords = "compression, information theory",
  url = "https://arxiv.org/abs/2102.09270"
}


@inproceedings{Agustsson2020a,
  author = "E. Agustsson and L. Theis",
  title = "Universally Quantized Neural Compression",
  year = 2020,
  booktitle = "Advances in Neural Information Processing Systems 33",
  keywords = "compression, deep learning, channel simulation",
  url = "https://arxiv.org/abs/2006.09952"
}


@inproceedings{Korshunova2019a,
  author = "I. Korshunova and H. Xiong and M. Fedoryszak and L. Theis",
  title = "Discriminative Topic Modeling with Logistic LDA",
  year = 2019,
  booktitle = "Advances in Neural Information Processing Systems 33",
  keywords = "lda, bayesian inference, topic modeling",
  url = "https://arxiv.org/abs/1909.01436"
}


@inproceedings{Nguyen-Phuoc2019a,
  author = "T. Nguyen-Phuoc and C. Li and L. Theis and C. Richardt and Y.-L. Yang",
  title = "HoloGAN: Unsupervised learning of 3D representations from natural images",
  year = 2019,
  booktitle = "International Conference on Computer Vision",
  keywords = "generative modeling, 3d, deep learning",
  url = "https://www.monkeyoverflow.com/#/hologan-unsupervised-learning-of-3d-representations-from-natural-images/"
}


@inproceedings{Storrs2018a,
  author = "K. Storrs and S. V. Leuven and S. Kojder and L. Theis and F. Huszár",
  title = "Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices",
  year = 2018,
  booktitle = "Picture Coding Symposium",
  keywords = "compression, perceptual quality, psychophysics",
  url = "https://arxiv.org/abs/1807.02175"
}


@unpublished{Theis2018a,
  author = "L. Theis and I. Korshunova and A. Tejani and F. Huszár",
  title = "Faster gaze prediction with dense networks and Fisher pruning",
  year = 2018,
  keywords = "pruning, fisher information, saliency",
  url = "https://arxiv.org/abs/1801.05787",
  note = "arXiv:1801.05787"
}


@inproceedings{Korshunova2016a,
  author = "I. Korshunova and W. Shi and J. Dambre and L. Theis",
  title = "Fast Face-swap Using Convolutional Neural Networks",
  year = 2017,
  booktitle = "International Conference on Computer Vision",
  month = "Oct",
  keywords = "face-swap, cagenet, deep learning",
  url = "https://arxiv.org/abs/1611.09577"
}


@inproceedings{Ledig2016a,
  author = "C. Ledig and L. Theis and F. Huszar and J. Caballero and A. Aitken and A. Tejani and J. Totz and Z. Wang and W. Shi",
  title = "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network",
  year = 2017,
  booktitle = "Computer Vision and Pattern Recognition",
  month = "Jul",
  keywords = "super-resolution, deep learning",
  url = "http://arxiv.org/abs/1609.04802"
}


@inproceedings{Theis2017a,
  author = "L. Theis and W. Shi and A. Cunningham and F. Huszár",
  title = "Lossy Image Compression with Compressive Autoencoders",
  year = 2017,
  booktitle = "International Conference on Learning Representations",
  keywords = "compression, deep learning",
  url = "https://openreview.net/pdf?id=rJiNwv9gg"
}


@inproceedings{Sønderby2016a,
  author = "C. Sønderby and J. Caballero and L. Theis and W. Shi and F. Huszár",
  title = "Amortised MAP Inference for Image Super-resolution",
  year = 2017,
  booktitle = "International Conference on Learning Representations",
  keywords = "super-resolution, deep learning",
  url = "https://arxiv.org/abs/1610.04490"
}


@article{Theis2015a,
  author = "L. Theis and P. Berens and E. Froudarakis and J. Reimer and M. Roman-Roson and T. Baden and T. Euler and A. S. Tolias and M. Bethge",
  title = "Benchmarking spike rate inference in population calcium imaging",
  year = 2016,
  journal = "Neuron",
  volume = 90,
  number = 3,
  pages = "471-482",
  month = "May",
  keywords = "two-photon imaging, spiking neurons",
  doi = "10.1016/j.neuron.2016.04.014",
  url = "http://www.cell.com/neuron/fulltext/S0896-6273(16)30073-3"
}


@inproceedings{Theis2016a,
  author = "L. Theis and A. van den Oord and M. Bethge",
  title = "A note on the evaluation of generative models",
  year = 2016,
  booktitle = "International Conference on Learning Representations",
  month = "Apr",
  keywords = "generative modeling",
  url = "http://arxiv.org/abs/1511.01844"
}


@phdthesis{Theis2016c,
  author = "L. Theis",
  title = "Advances in Probabilistic Modeling of Natural Images",
  year = 2016,
  note = "PhD thesis"
}


@inproceedings{Theis2015c,
  author = "L. Theis and M. Bethge",
  title = "Generative Image Modeling Using Spatial LSTMs",
  year = 2015,
  booktitle = "Advances in Neural Information Processing Systems 28",
  month = "Dec",
  keywords = "deep learning, generative modeling, natural image statistics, lstm, mcgsm",
  url = "http://arxiv.org/abs/1506.03478/"
}


@inproceedings{Theis2015b,
  author = "L. Theis and M. D. Hoffman",
  title = "A trust-region method for stochastic variational inference with applications to streaming data",
  year = 2015,
  booktitle = "Proceedings of the 32nd International Conference on Machine Learning",
  month = "Jul",
  keywords = "lda, streaming, svi, bayesian inference, topic modeling",
  url = "http://arxiv.org/abs/1505.07649/"
}


@inproceedings{Kümmerer2014b,
  author = "M. Kümmerer and L. Theis and M. Bethge",
  title = "Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet",
  year = 2015,
  booktitle = "ICLR Workshop",
  month = "Jun",
  keywords = "saliency, deep learning",
  url = "http://arxiv.org/abs/1411.1045"
}


@incollection{Gerhard2015a,
  author = "H. E. Gerhard and L. Theis and M. Bethge",
  title = "Modeling Natural Image Statistics",
  year = 2015,
  booktitle = "Biologically-inspired Computer Vision—Fundamentals and Applications",
  publisher = "Wiley VCH",
  keywords = "natural image statistics, mcgsm, ica, psychophysics",
  url = "http://www.amazon.de/Biologically-Inspired-Computer-Vision-Fundamentals-Applications/dp/3527412646/",
  isbn = "978-3527412648"
}


@inproceedings{Sra2015a,
  author = "S. Sra and R. Hosseini and L. Theis and M. Bethge",
  title = "Data modeling with the elliptical gamma distribution",
  year = 2015,
  booktitle = "Artificial Intelligence and Statistics",
  volume = 18,
  keywords = "density estimation, natural image statistics, mixture modeling",
  url = "http://www.jmlr.org/proceedings/papers/v38/sra15.pdf"
}


@article{Chagas2013a,
  author = "A. M. Chagas and L. Theis and B. Sengupta and M. Stüttgen and M. Bethge and C. Schwarz",
  title = "Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents",
  year = 2013,
  journal = "Frontiers in Neural Circuits",
  volume = 7,
  number = 190,
  month = "Dec",
  keywords = "neuroscience, spiking neurons",
  url = "http://www.frontiersin.org/Journal/10.3389/fncir.2013.00190/abstract"
}


@article{Theis2013a,
  author = "L. Theis and A. M. Chagas and D. Arnstein and C. Schwarz and M. Bethge",
  title = "Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification",
  year = 2013,
  journal = "PLoS Computational Biology",
  volume = 9,
  number = 11,
  month = "Nov",
  keywords = "generalized linear model, spiking neurons, mixture models, generative modeling",
  doi = "10.1371/journal.pcbi.1003356",
  url = "http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003356"
}


@inproceedings{Theis2012d,
  author = "L. Theis and J. Sohl-Dickstein and M. Bethge",
  title = "Training sparse natural image models with a fast Gibbs sampler of an extended state space",
  year = 2012,
  booktitle = "Advances in Neural Information Processing Systems 25",
  month = "Nov",
  keywords = "natural image statistics, ica, overcompleteness, bayesian inference"
}


@article{Theis2012a,
  author = "L. Theis and R. Hosseini and M. Bethge",
  title = "Mixtures of Conditional Gaussian Scale Mixtures Applied to Multiscale Image Representations",
  year = 2012,
  journal = "PLoS ONE",
  publisher = "Public Library of Science",
  volume = 7,
  number = 7,
  month = "Jul",
  keywords = "natural image statistics, random fields, mcgsm, mixture models",
  doi = "10.1371/journal.pone.0039857",
  url = "http://bethgelab.org/code/theis2012/"
}


@article{Theis2011a,
  author = "L. Theis and S. Gerwinn and F. Sinz and M. Bethge",
  title = "In All Likelihood, Deep Belief Is Not Enough",
  year = 2011,
  journal = "Journal of Machine Learning Research",
  volume = 12,
  month = "Nov",
  keywords = "natural image statistics, deep belief networks, boltzmann machines, deep learning"
}