Josip Djolonga | DeepAI

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∙ 07/12/2023

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

The ubiquitous and demonstrably suboptimal choice of resizing images to ...

0 Mostafa Dehghani, et al. ∙

∙ 04/24/2023

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

The most performant spatio-temporal action localisation models use exter...

0 Alexey Gritsenko, et al. ∙

∙ 02/02/2023

Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective

The top-k operator returns a k-sparse vector, where the non-zero values ...

0 Michael E. Sander, et al. ∙

∙ 07/08/2022

Beyond Transfer Learning: Co-finetuning for Action Localisation

Transfer learning is the predominant paradigm for training deep networks...

9 Anurag Arnab, et al. ∙

∙ 06/15/2021

Revisiting the Calibration of Modern Neural Networks

Accurate estimation of predictive uncertainty (model calibration) is ess...

18 Matthias Minderer, et al. ∙

∙ 06/07/2021

Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning

High-quality estimates of uncertainty and robustness are crucial for num...

0 Zachary Nado, et al. ∙

∙ 04/09/2021

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

Before deploying machine learning models it is critical to assess their ...

10 Jessica Yung, et al. ∙

∙ 10/06/2020

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

We propose a method to learn image representations from uncurated videos...

6 Rob Romijnders, et al. ∙

∙ 07/16/2020

On Robustness and Transferability of Convolutional Neural Networks

Modern deep convolutional networks (CNNs) are often criticized for not g...

15 Josip Djolonga, et al. ∙

∙ 02/20/2020

Fast Differentiable Sorting and Ranking

The sorting operation is one of the most basic and commonly used buildin...

0 Mathieu Blondel, et al. ∙

∙ 12/05/2019

Self-Supervised Learning of Video-Induced Visual Invariances

We propose a general framework for self-supervised learning of transfera...

14 Michael Tschannen, et al. ∙

∙ 07/31/2019

On Mutual Information Maximization for Representation Learning

Many recent methods for unsupervised or self-supervised representation l...

0 Michael Tschannen, et al. ∙

∙ 05/27/2019

Practical and Consistent Estimation of f-Divergences

The estimation of an f-divergence between two probability distributions ...

0 Paul K. Rubenstein, et al. ∙

∙ 05/26/2019

Evaluating Generative Models Using Divergence Frontiers

Despite the tremendous progress in the estimation of generative models, ...

0 Josip Djolonga, et al. ∙

∙ 09/04/2017

Learning Implicit Generative Models Using Differentiable Graph Tests

Recently, there has been a growing interest in the problem of learning r...

0 Josip Djolonga, et al. ∙

∙ 02/23/2015

Scalable Variational Inference in Log-supermodular Models

We consider the problem of approximate Bayesian inference in log-supermo...

0 Josip Djolonga, et al. ∙

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