Mario Lucic

Krzysztof Marcin Choromanski

Richard Szeliski

Jonathan T. Barron

ACM Trans. Graph., July, 2024

End-to-End Spatio-Temporal Action Localisation with Video Transformers.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

On Scaling Up a Multilingual Vision and Language Model.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

PolyViT: Co-training Vision Transformers on Images, Videos and Audio.

[BibT_eX]

[DOI]

Valerii Likhosherstov

Anurag Arnab

Mariana-Iuliana Georgescu

Yi Tay

Mostafa Dehghani

Trans. Mach. Learn. Res., 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution.

[BibT_eX]

[DOI]

Ibrahim M. Alabdulmohsin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scaling Vision Transformers to 22 Billion Parameters.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Video OWL-ViT: Temporally-consistent open-world localization in video.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Audiovisual Masked Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

RUST: Latent Neural Scene Representations from Unposed Imagery.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Beyond Transfer Learning: Co-finetuning for Action Localisation.

[BibT_eX]

[DOI]

CoRR, 2022

Object Scene Representation Transformer.

[BibT_eX]

[DOI]

Mehdi S. M. Sajjadi

Daniel Duckworth

Aravindh Mahendran

Sjoerd van Steenkiste

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

VCT: A Video Compression Transformer.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Which Model to Transfer? Finding the Needle in the Growing Haystack.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

PolyViT: Co-training Vision Transformers on Images, Videos and Audio.

[BibT_eX]

[DOI]

Valerii Likhosherstov

Anurag Arnab

Krzysztof Choromanski

CoRR, 2021

SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

MLP-Mixer: An all-MLP Architecture for Vision.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Revisiting the Calibration of Modern Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models.

[BibT_eX]

[DOI]

Ibrahim M. Alabdulmohsin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ViViT: A Video Vision Transformer.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

On Robustness and Transferability of Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

On Mutual Information Maximization for Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Self-Supervised Learning of Video-Induced Visual Invariances.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Precision-Recall Curves Using Information Divergence Frontiers.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A Commentary on the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Semantic Bottleneck Scene Generation.

[BibT_eX]

[DOI]

CoRR, 2019

The Visual Task Adaptation Benchmark.

[BibT_eX]

[DOI]

CoRR, 2019

Evaluating Generative Models Using Divergence Frontiers.

[BibT_eX]

[DOI]

CoRR, 2019

High-Fidelity Image Generation With Fewer Labels.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

A Large-Scale Study on Regularization and Normalization in GANs.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

On Self Modulation for Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Self-Supervised GANs via Auxiliary Rotation Loss.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Recent Advances in Autoencoder-Based Representation Learning.

[BibT_eX]

[DOI]

Michael Tschannen

CoRR, 2018

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

CoRR, 2018

Self-Supervised Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2018

The GAN Landscape: Losses, Architectures, Regularization, and Normalization.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Generative Models for Distribution-Preserving Lossy Compression.

[BibT_eX]

[DOI]

Michael Tschannen

Eirikur Agustsson

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Assessing Generative Models via Precision and Recall.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Are GANs Created Equal? A Large-Scale Study.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable k -Means Clustering via Lightweight Coresets.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

One-shot Coresets: The Case of k-Clustering.

[BibT_eX]

[DOI]

Silvio Lattanzi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Computational and Statistical Tradeoffs via Data Summarization.

[BibT_eX]

[DOI]

PhD thesis, 2017

Training Gaussian Mixture Models at Scale via Coresets.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

Uniform Deviation Bounds for Unbounded Loss Functions like k-Means.

[BibT_eX]

[DOI]

CoRR, 2017

Scalable and Distributed Clustering via Lightweight Coresets.

[BibT_eX]

[DOI]

CoRR, 2017

Stochastic Submodular Maximization: The Case of Coverage Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Uniform Deviation Bounds for k-Means Clustering.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Distributed and Provably Good Seedings for k-Means in Constant Rounds.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Fast and Provably Good Seedings for k-Means.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Linear-Time Outlier Detection via Sensitivity.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Horizontally Scalable Submodular Maximization.

[BibT_eX]

[DOI]

Morteza Zadimoghaddam

Proceedings of the 33nd International Conference on Machine Learning, 2016

Quantifying Location Privacy Leakage from Transaction Prices.

[BibT_eX]

[DOI]

Proceedings of the Computer Security - ESORICS 2016, 2016

Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Approximate K-Means++ in Sublinear Time.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Quantifying Location Privacy Leakage from Transaction Prices.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2015

Coresets for Nonparametric Estimation - the Case of DP-Means.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning.

[BibT_eX]

[DOI]

Mesrob I. Ohannessian

Amin Karbasi