Michael Tschannen
31 papers · 2016–2025 · 8 venues · across top CS/AI venues
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Achievements
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(10)
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Deep Specialist
(10)
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Conference Pioneer
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Renaissance Researcher
(5)
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Trend Setter
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(128)
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Research topics
Deep Learning
(23)
Machine Learning
(21)
Computer Vision
(14)
Models
(12)
Learning Types Β· Machine Learning
(11)
Learning Types Β· Deep Learning
(10)
Architectures
(9)
Artificial Intelligence
(8)
Application Areas
(8)
Processing
(7)
Core AI Β· Artificial Intelligence
(6)
Core Methods
(6)
Generation
(5)
Core AI Β· Computer Vision
(4)
Optimization & Theory
(4)
Keywords
representation learning
(6)
image compression
(5)
self-supervised learning
(5)
image classification
(4)
convolutional neural network
(4)
transfer learning
(4)
entropy coding
(3)
image generation
(3)
model scaling
(3)
image captioning
(3)
lossy compression
(3)
generative adversarial network
(3)
vision-language model
(3)
neural network
(3)
out-of-distribution generalization
(2)
vector quantization
(2)
few-shot learning
(2)
contrastive learning
(2)
matching pursuit
(2)
vision transformer
(2)
Papers
JetFormer: An autoregressive generative model of raw images and text
ICLR 2025
Finite Scalar Quantization: VQ-VAE Made Simple
ICLR 2024
GIVT: Generative Infinite-Vocabulary Transformers
ECCV 2024
LocCa: Visual Pretraining with Location-aware Captioners
NeurIPS 2024
On Scaling Up a Multilingual Vision and Language Model
CVPR 2024
CLIPPO: Image-and-Language Understanding From Pixels Only
CVPR 2023
FlexiViT: One Model for All Patch Sizes
CVPR 2023
Image Captioners Are Scalable Vision Learners Too
NeurIPS 2023
M2T: Masking Transformers Twice for Faster Decoding
ICCV 2023
Scaling Vision Transformers to 22 Billion Parameters
ICML 2023
On Robustness and Transferability of Convolutional Neural Networks
CVPR 2021
Representation Learning From Videos In-the-Wild: An Object-Centric Approach
WACV 2021
Automatic Shortcut Removal for Self-Supervised Representation Learning
ICML 2020
Disentangling Factors of Variations Using Few Labels
ICLR 2020
High-Fidelity Generative Image Compression
NeurIPS 2020
Learning Better Lossless Compression Using Lossy Compression
CVPR 2020
On Mutual Information Maximization for Representation Learning
ICLR 2020
Self-Supervised Learning of Video-Induced Visual Invariances
CVPR 2020
Weakly-Supervised Disentanglement Without Compromises
ICML 2020
Generative Adversarial Networks for Extreme Learned Image Compression
ICCV 2019
High-Fidelity Image Generation With Fewer Labels
ICML 2019
Practical Full Resolution Learned Lossless Image Compression
CVPR 2019
Born Again Neural Networks
ICML 2018
Conditional Probability Models for Deep Image Compression
CVPR 2018
Deep Generative Models for Distribution-Preserving Lossy Compression
NeurIPS 2018
StrassenNets: Deep Learning with a Multiplication Budget
ICML 2018
Towards Image Understanding from Deep Compression Without Decoding
ICLR 2018
A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe
AISTATS 2017
Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees
NeurIPS 2017
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
NeurIPS 2017
Discrete Deep Feature Extraction: A Theory and New Architectures
ICML 2016