Extended Texture Prediction for H.264/AVC Intra Coding. - Johannes Ballé; Mathias Wien (ICIP (6), 2007)

Component-based image coding using non-local means filtering and an autoregressive texture model. - Johannes Ballé; Bastian Jurczyk; Aleksandar Stojanovic 002 (ICIP, 2009)

MATLAB Meets LEGO Mindstorms - A Freshman Introduction Course Into Practical Engineering. - Alexander Behrens; Linus Atorf; Robert Schwann; Bernd Neumann; Rainer Schnitzler; Johannes Ballé; Thomas Herold; Aulis Telle; Tobias G. Noll; Kay Hameyer; Til Aach (IEEE Trans. Educ., 2010)

Improved entropy coding for component-based image coding. - Christian Feldmann; Johannes Ballé (ICIP, 2011)

Models for Static and Dynamic Texture Synthesis in Image and Video Compression. - Johannes Ballé; Aleksandar Stojanovic 002; Jens-Rainer Ohm (IEEE J. Sel. Top. Signal Process., 2011)

Subjective evaluation of texture similarity metrics for compression applications. - Johannes Ballé (PCS, 2012)

Median trilateral loop filter for depth map video coding. - Fabian Jäger; Johannes Ballé (PCS, 2012)

Efficient shift-variant image restoration using deformable filtering (Part II): PSF field estimation. - David Miraut 001; Johannes Ballé; Javier Portilla (EURASIP J. Adv. Signal Process., 2012)

Image compression by microtexture synthesis. - Johannes Ballé (Shaker, 2012)

Learning sparse filter bank transforms with convolutional ICA. - Johannes Ballé; Eero P. Simoncelli (ICIP, 2014)

The local low-dimensionality of natural images. - Olivier J. Hénaff; Johannes Ballé; Neil C. Rabinowitz; Eero P. Simoncelli (ICLR, 2015)

Perceptual image quality assessment using a normalized Laplacian pyramid. - Valero Laparra; Johannes Ballé; Alexander Berardino; Eero P. Simoncelli (HVEI, 2016)

End-to-end optimization of nonlinear transform codes for perceptual quality. - Johannes Ballé; Valero Laparra; Eero P. Simoncelli (PCS, 2016)

Density Modeling of Images using a Generalized Normalization Transformation. - Johannes Ballé; Valero Laparra; Eero P. Simoncelli (ICLR, 2016)

End-to-end Optimized Image Compression. - Johannes Ballé; Valero Laparra; Eero P. Simoncelli (ICLR, 2017)

Eigen-Distortions of Hierarchical Representations. - Alexander Berardino; Valero Laparra; Johannes Ballé; Eero P. Simoncelli (NIPS, 2017)

Perceptually Optimized Image Rendering. - Valero Laparra; Alexander Berardino; Johannes Ballé; Eero P. Simoncelli (CoRR, 2017)

Towards A Semantic Perceptual Image Metric. - Troy T. Chinen; Johannes Ballé; Chunhui Gu; Sung Jin Hwang; Sergey Ioffe; Nick Johnston; Thomas Leung; David Minnen; Sean M. O'Malley; Charles Rosenberg 001; George Toderici (ICIP, 2018)

Variational image compression with a scale hyperprior. - Johannes Ballé; David Minnen; Saurabh Singh; Sung Jin Hwang; Nick Johnston (ICLR (Poster), 2018)

Joint Autoregressive and Hierarchical Priors for Learned Image Compression. - David Minnen; Johannes Ballé; George Toderici (NeurIPS, 2018)

Efficient Nonlinear Transforms for Lossy Image Compression. - Johannes Ballé (PCS, 2018)

Integer Networks for Data Compression with Latent-Variable Models. - Johannes Ballé; Nick Johnston; David Minnen (ICLR (Poster), 2019)

Accelerating Training of Deep Neural Networks with a Standardization Loss. - Jasmine Collins; Johannes Ballé; Jonathon Shlens (CoRR, 2019)

Model Compression by Entropy Penalized Reparameterization. - Deniz Oktay; Johannes Ballé; Saurabh Singh; Abhinav Shrivastava (CoRR, 2019)

Computationally Efficient Neural Image Compression. - Nick Johnston; Elad Eban; Ariel Gordon; Johannes Ballé (CoRR, 2019)

Scale-Space Flow for End-to-End Optimized Video Compression. - Eirikur Agustsson; David Minnen; Nick Johnston; Johannes Ballé; Sung Jin Hwang; George Toderici (CVPR, 2020)

End-to-End Learning of Compressible Features. - Saurabh Singh; Sami Abu-El-Haija; Nick Johnston; Johannes Ballé; Abhinav Shrivastava; George Toderici (ICIP, 2020)

Scalable Model Compression by Entropy Penalized Reparameterization. - Deniz Oktay; Johannes Ballé; Saurabh Singh; Abhinav Shrivastava (ICLR, 2020)

An Unsupervised Information-Theoretic Perceptual Quality Metric. - Sangnie Bhardwaj; Ian Fischer; Johannes Ballé; Troy T. Chinen (NeurIPS, 2020)

Neural Networks Optimally Compress the Sawbridge. - Aaron B. Wagner; Johannes Ballé (DCC, 2021)

3D Scene Compression through Entropy Penalized Neural Representation Functions. - Thomas Bird; Johannes Ballé; Saurabh Singh; Philip A. Chou (PCS, 2021)

Towards Generative Video Compression. - Fabian Mentzer; Eirikur Agustsson; Johannes Ballé; David Minnen; Nick Johnston; George Toderici (CoRR, 2021)

Nonlinear Transform Coding. - Johannes Ballé; Philip A. Chou; David Minnen; Saurabh Singh; Nick Johnston; Eirikur Agustsson; Sung Jin Hwang; George Toderici (IEEE J. Sel. Top. Signal Process., 2021)

Optimal Compression of Locally Differentially Private Mechanisms. - Abhin Shah; Wei-Ning Chen; Johannes Ballé; Peter Kairouz; Lucas Theis (AISTATS, 2022)

Hyperspectral remote sensing data compression with neural networks. - Sebastià Mijares i Verdú; Johannes Ballé; Valero Laparra; Joan Bartrina-Rapesta; Miguel Hernández-Cabronero; Joan Serra-Sagristà (DCC, 2022)

Neural Video Compression Using GANs for Detail Synthesis and Propagation. - Fabian Mentzer; Eirikur Agustsson; Johannes Ballé; David Minnen; Nick Johnston; George Toderici (ECCV (26), 2022)

On the relation between statistical learning and perceptual distances. - Alexander Hepburn; Valero Laparra; Raúl Santos-Rodríguez; Johannes Ballé; Jesus Malo (ICLR, 2022)

Do Neural Networks Compress Manifolds Optimally? - Sourbh Bhadane; Aaron B. Wagner; Johannes Ballé (ITW, 2022)

Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory. - Nicole Mitchell; Johannes Ballé; Zachary Charles; Jakub Konecný (CoRR, 2022)

A Rate-Distortion View on Model Updates. - Nicole Mitchell; Johannes Ballé; Zachary Charles; Jakub Konecný (Tiny Papers @ ICLR, 2023)

Learned Wyner-Ziv Compressors Recover Binning. - Ezgi Özyilkan; Johannes Ballé; Elza Erkip (ISIT, 2023)

A Scalable Reduced-Complexity Compression of Hyperspectral Remote Sensing Images Using Deep Learning. - Sebastià Mijares i Verdú; Johannes Ballé; Valero Laparra; Joan Bartrina-Rapesta; Miguel Hernández-Cabronero; Joan Serra-Sagristà (Remote. Sens., 2023)

Wasserstein Distortion: Unifying Fidelity and Realism. - Yang Qiu; Aaron B. Wagner; Johannes Ballé; Lucas Theis (CISS, 2024)

The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric. - Daniel Severo 001; Lucas Theis; Johannes Ballé (ICLR, 2024)

Fourier Basis Density Model. - Alfredo De la Fuente; Saurabh Singh; Johannes Ballé (PCS, 2024)

Neural Distributed Compressor Discovers Binning. - Ezgi Özyilkan; Johannes Ballé; Elza Erkip (IEEE J. Sel. Areas Inf. Theory, 2024)

Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion. - Jona Ballé; Luca Versari; Emilien Dupont; Hyunjik Kim; Matthias Bauer (CVPR, 2025)

Discretized Approximate Ancestral Sampling. - Alfredo De la Fuente; Saurabh Singh; Jona Ballé (ISIT, 2025)

Learning a distance measure from the information-estimation geometry of data. - Guy Ohayon; Pierre-Étienne H. Fiquet; Florentin Guth; Jona Ballé; Eero P. Simoncelli (CoRR, 2025)