Alexander Kolesnikov
20 papers · 2017–2025 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
(17)
Deep Learning
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Computer Vision
(7)
Core Methods
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Learning Types Β· Deep Learning
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Keywords
image classification
(7)
vision transformer
(7)
transfer learning
(5)
model scaling
(4)
convolutional neural network
(3)
computer vision
(3)
contrastive learning
(2)
autoregressive model
(2)
self-supervised learning
(2)
few-shot learning
(2)
visual question answering
(2)
representation learning
(2)
image captioning
(2)
zero-shot transfer
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domain generalization
(1)
reinforcement learning
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policy optimization
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image generation
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unsupervised learning
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model robustness
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Papers
JetFormer: An autoregressive generative model of raw images and text
ICLR 2025
On Scaling Up a Multilingual Vision and Language Model
CVPR 2024
FlexiViT: One Model for All Patch Sizes
CVPR 2023
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
NeurIPS 2023
PaLI: A Jointly-Scaled Multilingual Language-Image Model
ICLR 2023
Scaling Vision Transformers to 22 Billion Parameters
ICML 2023
Sigmoid Loss for Language Image Pre-Training
ICCV 2023
Tuning Computer Vision Models With Task Rewards
ICML 2023
Knowledge Distillation: A Good Teacher Is Patient and Consistent
CVPR 2022
LiT: Zero-Shot Transfer With Locked-Image Text Tuning
CVPR 2022
Scaling Vision Transformers
CVPR 2022
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes
NeurIPS 2022
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
ICLR 2021
MLP-Mixer: An all-MLP Architecture for Vision
NeurIPS 2021
On Robustness and Transferability of Convolutional Neural Networks
CVPR 2021
Big Transfer (BiT): General Visual Representation Learning
ECCV 2020
Revisiting Self-Supervised Visual Representation Learning
CVPR 2019
S4L: Self-Supervised Semi-Supervised Learning
ICCV 2019
iCaRL: Incremental Classifier and Representation Learning
CVPR 2017
PixelCNN Models with Auxiliary Variables for Natural Image Modeling
ICML 2017