Dan Busbridge | DeepAI

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∙ 09/07/2023

REALM: Robust Entropy Adaptive Loss Minimization for Improved Single-Sample Test-Time Adaptation

Fully-test-time adaptation (F-TTA) can mitigate performance loss due to ...

0 Skyler Seto, et al. ∙

∙ 07/25/2023

How to Scale Your EMA

Preserving training dynamics across batch sizes is an important tool for...

0 Dan Busbridge, et al. ∙

∙ 07/20/2023

The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning

The mechanisms behind the success of multi-view self-supervised learning...

0 Borja Rodríguez Gálvez, et al. ∙

∙ 06/28/2023

DUET: 2D Structured and Approximately Equivariant Representations

Multiview Self-Supervised Learning (MSSL) is based on learning invarianc...

0 Xavier Suau, et al. ∙

∙ 03/11/2023

Stabilizing Transformer Training by Preventing Attention Entropy Collapse

Training stability is of great importance to Transformers. In this work,...

5 Shuangfei Zhai, et al. ∙

∙ 10/28/2022

Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer

Self-supervised representation learning (SSL) methods provide an effecti...

0 Andrius Ovsianas, et al. ∙

∙ 07/15/2022

Position Prediction as an Effective Pretraining Strategy

Transformers have gained increasing popularity in a wide range of applic...

1 Shuangfei Zhai, et al. ∙

∙ 02/27/2022

The Impact of Explanations on Layperson Trust in Artificial Intelligence-Driven Symptom Checker Apps: Experimental Study

To achieve the promoted benefits of an AI symptom checker, laypeople mus...

0 Claire Woodcock, et al. ∙

∙ 10/01/2021

Stochastic Contrastive Learning

While state-of-the-art contrastive Self-Supervised Learning (SSL) models...

0 Jason Ramapuram, et al. ∙

∙ 10/01/2021

Evaluating the fairness of fine-tuning strategies in self-supervised learning

In this work we examine how fine-tuning impacts the fairness of contrast...

0 Jason Ramapuram, et al. ∙

∙ 10/01/2021

Do Self-Supervised and Supervised Methods Learn Similar Visual Representations?

Despite the success of a number of recent techniques for visual self-sup...

0 Tom George Grigg, et al. ∙

∙ 07/27/2020

Neural Temporal Point Processes For Modelling Electronic Health Records

The modelling of Electronic Health Records (EHRs) has the potential to d...

0 Joseph Enguehard, et al. ∙

∙ 03/28/2020

Learning medical triage from clinicians using Deep Q-Learning

Medical Triage is of paramount importance to healthcare systems, allowin...

8 Albert Buchard, et al. ∙

∙ 10/04/2019

Neural Language Priors

The choice of sentence encoder architecture reflects assumptions about h...

0 Joseph Enguehard, et al. ∙

∙ 04/11/2019

Relational Graph Attention Networks

We investigate Relational Graph Attention Networks, a class of models th...

12 Dan Busbridge, et al. ∙

∙ 05/09/2018

Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks

Experimental evidence indicates that simple models outperform complex de...

0 Vitalii Zhelezniak, et al. ∙

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