← Authors

Mario Lucic

42 papers · 2014–2024 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) πŸ—ΊοΈ Taxonomy Completionist (72) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (10) 🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🀝 Dynamic Duo (13) πŸ‘₯ Mega-Team (43) 🧬 Topic Evolution πŸ’Ž Century Club (42) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (164) ⚑ Prolific Year (6) ❓ The Questioner (2) πŸ”₯ Unstoppable (11)

Conferences

NIPS (12) CVPR (8) ICML (8) AISTATS (4) ICCV (3) JMLR (3) ICLR (2) IJCAI (1) WACV (1)

Top co-authors

Olivier Bachem (13) Sylvain Gelly (11) Neil Houlsby (11) Andreas Krause (10) Josip Djolonga (10) Xiaohua Zhai (9) Michael Tschannen (8) Matthias Minderer (6) Marvin Ritter (5) Aravindh Mahendran (5)

Keywords

representation learning (6) unsupervised learning (5) generative adversarial network (5) transfer learning (5) self-supervised learning (5) vision transformer (4) k-means clustering (4) 3d reconstruction (3) model scaling (3) video understanding (3) object detection (3) generative model (3) novel view synthesis (3) distribution shift (2) out-of-distribution generalization (2) transformer architecture (2) video transformer (2) data summarization (2) multimodal learning (2) image classification (2)

Papers

End-to-End Spatio-Temporal Action Localisation with Video Transformers CVPR 2024
On Scaling Up a Multilingual Vision and Language Model CVPR 2024
Video OWL-ViT: Temporally-consistent Open-world Localization in Video ICCV 2023
Patch n’ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution NIPS 2023
RUST: Latent Neural Scene Representations From Unposed Imagery CVPR 2023
Scaling Vision Transformers to 22 Billion Parameters ICML 2023
Audiovisual Masked Autoencoders ICCV 2023
VCT: A Video Compression Transformer NIPS 2022
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations CVPR 2022
Object Scene Representation Transformer NIPS 2022
Which Model To Transfer? Finding the Needle in the Growing Haystack CVPR 2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning JMLR 2022
Representation Learning From Videos In-the-Wild: An Object-Centric Approach WACV 2021
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models NIPS 2021
Revisiting the Calibration of Modern Neural Networks NIPS 2021
MLP-Mixer: An all-MLP Architecture for Vision NIPS 2021
On Robustness and Transferability of Convolutional Neural Networks CVPR 2021
ViViT: A Video Vision Transformer ICCV 2021
Self-Supervised Learning of Video-Induced Visual Invariances CVPR 2020
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation JMLR 2020
Precision-Recall Curves Using Information Divergence Frontiers AISTATS 2020
On Mutual Information Maximization for Representation Learning ICLR 2020
High-Fidelity Image Generation With Fewer Labels ICML 2019
Self-Supervised GANs via Auxiliary Rotation Loss CVPR 2019
On Self Modulation for Generative Adversarial Networks ICLR 2019
A Large-Scale Study on Regularization and Normalization in GANs ICML 2019
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations ICML 2019
Deep Generative Models for Distribution-Preserving Lossy Compression NIPS 2018
Training Gaussian Mixture Models at Scale via Coresets JMLR 2018
One-shot Coresets: The Case of k-Clustering AISTATS 2018
Assessing Generative Models via Precision and Recall NIPS 2018
Are GANs Created Equal? A Large-Scale Study NIPS 2018
Stochastic Submodular Maximization: The Case of Coverage Functions NIPS 2017
Uniform Deviation Bounds for k-Means Clustering ICML 2017
Distributed and Provably Good Seedings for k-Means in Constant Rounds ICML 2017
Horizontally Scalable Submodular Maximization ICML 2016
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures AISTATS 2016
Fast and Provably Good Seedings for k-Means NIPS 2016
Linear-Time Outlier Detection via Sensitivity IJCAI 2016
Coresets for Nonparametric Estimation - the Case of DP-Means ICML 2015
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning AISTATS 2015
Fast and Robust Least Squares Estimation in Corrupted Linear Models NIPS 2014