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papers

Publications (51)

cs.LG2018

Noisy subspace clustering via matching pursuits

Michael Tschannen, Helmut Bölcskei

eess.IV2020

High-Fidelity Generative Image Compression

Fabian Mentzer, George Toderici, Michael Tschannen +1

cs.LG2017

A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe

Francesco Locatello, Rajiv Khanna, Michael Tschannen +1

cs.CV2021

Representation learning from videos in-the-wild: An object-centric approach

Rob Romijnders, Aravindh Mahendran, Michael Tschannen +4

cs.LG2018

StrassenNets: Deep Learning with a Multiplication Budget

Michael Tschannen, Aran Khanna, Anima Anandkumar

cs.CV2024

GIVT: Generative Infinite-Vocabulary Transformers

Michael Tschannen, Cian Eastwood, Fabian Mentzer

eess.IV2023

M2T: Masking Transformers Twice for Faster Decoding

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen

cs.CV2020

Self-Supervised Learning of Video-Induced Visual Invariances

Michael Tschannen, Josip Djolonga, Marvin Ritter +5

stat.ML2015

Nonparametric Nearest Neighbor Random Process Clustering

Michael Tschannen, Helmut Bölcskei

cs.LG2019

Semantic Bottleneck Scene Generation

Samaneh Azadi, Michael Tschannen, Eric Tzeng +3

cs.CV2023

PaLI-X: On Scaling up a Multilingual Vision and Language Model

Xi Chen, Josip Djolonga, Piotr Padlewski +40

cs.LG2020

Weakly-Supervised Disentanglement Without Compromises

Francesco Locatello, Ben Poole, Gunnar Rätsch +3

cs.LG2019

High-Fidelity Image Generation With Fewer Labels

Mario Lucic, Michael Tschannen, Marvin Ritter +3

cs.LG2017

Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees

Francesco Locatello, Michael Tschannen, Gunnar Rätsch +1

cs.CV2020

Learning Better Lossless Compression Using Lossy Compression

Fabian Mentzer, Luc Van Gool, Michael Tschannen

cs.CV2017

Deep Structured Features for Semantic Segmentation

Michael Tschannen, Lukas Cavigelli, Fabian Mentzer +2

cs.LG2017

Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations

Eirikur Agustsson, Fabian Mentzer, Michael Tschannen +4

cs.LG2018

Recent Advances in Autoencoder-Based Representation Learning

Michael Tschannen, Olivier Bachem, Mario Lucic

cs.LG2016

Discrete Deep Feature Extraction: A Theory and New Architectures

Thomas Wiatowski, Michael Tschannen, Aleksandar Stanić +2

cs.LG2018

Deep Generative Models for Distribution-Preserving Lossy Compression

Michael Tschannen, Eirikur Agustsson, Mario Lucic

cs.LG2017

Robust nonparametric nearest neighbor random process clustering

Michael Tschannen, Helmut Bölcskei

cs.LG2020

Disentangling Factors of Variation Using Few Labels

Francesco Locatello, Michael Tschannen, Stefan Bauer +3

cs.LG2025

JetFormer: An Autoregressive Generative Model of Raw Images and Text

Michael Tschannen, André Susano Pinto, Alexander Kolesnikov

cs.CV2023

Image Captioners Are Scalable Vision Learners Too

Michael Tschannen, Manoj Kumar, Andreas Steiner +3

cs.CV2024

PaliGemma: A versatile 3B VLM for transfer

Lucas Beyer, Andreas Steiner, André Susano Pinto +32

cs.CV2024

PaliGemma 2: A Family of Versatile VLMs for Transfer

Andreas Steiner, André Susano Pinto, Michael Tschannen +15

cs.CV2019

Conditional Probability Models for Deep Image Compression

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen +2

cs.CL2025

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431

cs.CV2018

Towards Image Understanding from Deep Compression without Decoding

Robert Torfason, Fabian Mentzer, Eirikur Agustsson +3

cs.CV2021

On Robustness and Transferability of Convolutional Neural Networks

Josip Djolonga, Jessica Yung, Michael Tschannen +11

cs.LG2020

On Mutual Information Maximization for Representation Learning

Michael Tschannen, Josip Djolonga, Paul K. Rubenstein +2

cs.CV2023

Finite Scalar Quantization: VQ-VAE Made Simple

Fabian Mentzer, David Minnen, Eirikur Agustsson +1

cs.CV2023

CLIPPO: Image-and-Language Understanding from Pixels Only

Michael Tschannen, Basil Mustafa, Neil Houlsby

cs.CV2023

Scaling Vision Transformers to 22 Billion Parameters

Mostafa Dehghani, Josip Djolonga, Basil Mustafa +39

cs.CV2025

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Michael Tschannen, Alexey Gritsenko, Xiao Wang +11

cs.CV2024

Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers

Aleksandar Stanić, Sergi Caelles, Michael Tschannen

cs.CV2023

FlexiViT: One Model for All Patch Sizes

Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov +7

cs.CV2022

Neural Face Video Compression using Multiple Views

Anna Volokitin, Stefan Brugger, Ali Benlalah +3

cs.CL2026

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

cs.IT2014

Subspace clustering of dimensionality-reduced data

Reinhard Heckel, Michael Tschannen, Helmut Bölcskei

cs.CV2024

LocCa: Visual Pretraining with Location-aware Captioners

Bo Wan, Michael Tschannen, Yongqin Xian +7

cs.CV2020

Automatic Shortcut Removal for Self-Supervised Representation Learning

Matthias Minderer, Olivier Bachem, Neil Houlsby +1

cs.CV2019

Generative Adversarial Networks for Extreme Learned Image Compression

Eirikur Agustsson, Michael Tschannen, Fabian Mentzer +2

stat.ML2015

Dimensionality-reduced subspace clustering

Reinhard Heckel, Michael Tschannen, Helmut Bölcskei

cs.LG2016

Pursuits in Structured Non-Convex Matrix Factorizations

Rajiv Khanna, Michael Tschannen, Martin Jaggi

cs.LG2025

Quantization-Free Autoregressive Action Transformer

Ziyad Sheebaelhamd, Michael Tschannen, Michael Muehlebach +1

cs.LG2018

Convolutional Recurrent Neural Networks for Electrocardiogram Classification

Martin Zihlmann, Dmytro Perekrestenko, Michael Tschannen

stat.ML2018

Born Again Neural Networks

Tommaso Furlanello, Zachary C. Lipton, Michael Tschannen +2

eess.IV2020

Practical Full Resolution Learned Lossless Image Compression

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen +2

cs.CV2020

A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark

Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov +14

cs.CV2024

Jet: A Modern Transformer-Based Normalizing Flow

Alexander Kolesnikov, André Susano Pinto, Michael Tschannen