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Mario Lucic

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

Achievements

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+12 more ↓ šŸ£ Hot Topic Early Bird šŸ Cross-Pollinator (15) šŸƒ Academic Marathon (10) šŸŒ Conference Polyglot (9) šŸŒˆ Renaissance Researcher (8)
šŸƒ Academic Marathon (10) šŸŒˆ Renaissance Researcher (8) šŸ§­ Keyword Pioneer šŸ¤ Dynamic Duo (13) šŸ‘„ Mega-Team (43) šŸ§¬ Topic Evolution šŸ’Ž Century Club (42) šŸ“ˆ Trend Setter šŸ—ƒļø Keyword Collector (164) āš” Prolific Year (6) ā“ The Questioner (2) šŸ”„ 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 nā€™ 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