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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 ...
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04/24/2023
End-to-End Spatio-Temporal Action Localisation with Video Transformers
The most performant spatio-temporal action localisation models use exter...
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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 ...
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07/08/2022
Beyond Transfer Learning: Co-finetuning for Action Localisation
Transfer learning is the predominant paradigm for training deep networks...
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06/15/2021
Revisiting the Calibration of Modern Neural Networks
Accurate estimation of predictive uncertainty (model calibration) is ess...
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06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
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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 ...
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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...
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07/16/2020
On Robustness and Transferability of Convolutional Neural Networks
Modern deep convolutional networks (CNNs) are often criticized for not g...
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02/20/2020
Fast Differentiable Sorting and Ranking
The sorting operation is one of the most basic and commonly used buildin...
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12/05/2019
Self-Supervised Learning of Video-Induced Visual Invariances
We propose a general framework for self-supervised learning of transfera...
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07/31/2019
On Mutual Information Maximization for Representation Learning
Many recent methods for unsupervised or self-supervised representation l...
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05/27/2019
Practical and Consistent Estimation of f-Divergences
The estimation of an f-divergence between two probability distributions ...
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05/26/2019
Evaluating Generative Models Using Divergence Frontiers
Despite the tremendous progress in the estimation of generative models, ...
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09/04/2017
Learning Implicit Generative Models Using Differentiable Graph Tests
Recently, there has been a growing interest in the problem of learning r...
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02/23/2015