← Authors

Josip Djolonga

23 papers · 2013–2024 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (61) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (11) 🌈 Renaissance Researcher (7) πŸ‘₯ Mega-Team (43) 🀝 Dynamic Duo (10) 🧬 Topic Evolution πŸ“ˆ Trend Setter ⚑ Prolific Year (5) πŸ’Ž Century Club (23) πŸ—ƒοΈ Keyword Collector (108) πŸ”₯ Unstoppable (9)

Conferences

NIPS (9) CVPR (4) ICML (4) AISTATS (2) ICLR (2) ICCV (1) WACV (1)

Top co-authors

Mario Lucic (10) Andreas Krause (9) Neil Houlsby (7) Michael Tschannen (6) Matthias Minderer (5) Mostafa Dehghani (4) Xiaohua Zhai (4) Joan Puigcerver (4) Sylvain Gelly (4) Marvin Ritter (3)

Keywords

variational inference (7) probabilistic modeling (4) object detection (3) transfer learning (3) model scaling (3) submodular optimization (3) markov random field (3) representation learning (3) few-shot learning (2) vision transformer (2) log-partition function (2) out-of-distribution generalization (2) convex optimization (2) bayesian inference (2) belief propagation (2) self-supervised learning (2) image segmentation (2) video understanding (2) partition function (2) submodular function (2)

Papers

On Scaling Up a Multilingual Vision and Language Model CVPR 2024
End-to-End Spatio-Temporal Action Localisation with Video Transformers CVPR 2024
Scaling Vision Transformers to 22 Billion Parameters ICML 2023
Patch n’ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution NIPS 2023
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective ICML 2023
Representation Learning From Videos In-the-Wild: An Object-Centric Approach WACV 2021
On Robustness and Transferability of Convolutional Neural Networks CVPR 2021
Revisiting the Calibration of Modern Neural Networks NIPS 2021
Self-Supervised Learning of Video-Induced Visual Invariances CVPR 2020
Precision-Recall Curves Using Information Divergence Frontiers AISTATS 2020
You Only Train Once: Loss-Conditional Training of Deep Networks ICLR 2020
On Mutual Information Maximization for Representation Learning ICLR 2020
Fast Differentiable Sorting and Ranking ICML 2020
Practical and Consistent Estimation of f-Divergences NIPS 2019
Provable Variational Inference for Constrained Log-Submodular Models NIPS 2018
Differentiable Learning of Submodular Models NIPS 2017
Variational Inference in Mixed Probabilistic Submodular Models NIPS 2016
Cooperative Graphical Models NIPS 2016
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation AISTATS 2016
Higher-Order Inference for Multi-Class Log-Supermodular Models ICCV 2015
Scalable Variational Inference in Log-supermodular Models ICML 2015
From MAP to Marginals: Variational Inference in Bayesian Submodular Models NIPS 2014
High-Dimensional Gaussian Process Bandits NIPS 2013