Josip Djolonga
23 papers · 2013–2024 · 7 venues · across top CS/AI venues
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Achievements
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(5)
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Research topics
Machine Learning
(18)
Deep Learning
(14)
Artificial Intelligence
(11)
Optimization & Theory
(11)
Mathematics & Optimization
(9)
Learning Types Β· Machine Learning
(7)
Optimization
(7)
Architectures
(6)
Bayesian & Probabilistic Β· Artificial Intelligence
(6)
Bayesian & Probabilistic Β· Machine Learning
(6)
Models
(6)
Computer Vision
(5)
Core AI
(4)
Core Methods
(4)
Learning Types Β· Deep Learning
(4)
Keywords
variational inference
(7)
probabilistic modeling
(4)
representation learning
(4)
transfer learning
(3)
self-supervised learning
(3)
markov random field
(3)
model scaling
(3)
submodular optimization
(3)
object detection
(3)
vision transformer
(2)
mutual information
(2)
log-partition function
(2)
determinantal point process
(2)
convex optimization
(2)
video understanding
(2)
out-of-distribution generalization
(2)
few-shot learning
(2)
belief propagation
(2)
bayesian inference
(2)
image segmentation
(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
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective
ICML 2023
Patch nβ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
NeurIPS 2023
Scaling Vision Transformers to 22 Billion Parameters
ICML 2023
On Robustness and Transferability of Convolutional Neural Networks
CVPR 2021
Representation Learning From Videos In-the-Wild: An Object-Centric Approach
WACV 2021
Revisiting the Calibration of Modern Neural Networks
NeurIPS 2021
Fast Differentiable Sorting and Ranking
ICML 2020
On Mutual Information Maximization for Representation Learning
ICLR 2020
Precision-Recall Curves Using Information Divergence Frontiers
AISTATS 2020
Self-Supervised Learning of Video-Induced Visual Invariances
CVPR 2020
You Only Train Once: Loss-Conditional Training of Deep Networks
ICLR 2020
Practical and Consistent Estimation of f-Divergences
NeurIPS 2019
Provable Variational Inference for Constrained Log-Submodular Models
NeurIPS 2018
Differentiable Learning of Submodular Models
NeurIPS 2017
Cooperative Graphical Models
NeurIPS 2016
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation
AISTATS 2016
Variational Inference in Mixed Probabilistic Submodular Models
NeurIPS 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
NeurIPS 2014
High-Dimensional Gaussian Process Bandits
NeurIPS 2013