5 citations · 8 across the 5 of their papers we have counts for
5 papers
Optimal predictive probability designs for randomized biomarker-guided oncology trials
Emily C. Zabor, Alexander M. Kaizer, Nathan A. Pennell +1
Efforts to develop biomarker-targeted anti-cancer therapies have progressed rapidly in recent years. Six antibodies acting on programmed death ligand 1 or programmed death 1 pathwa…
Efficient Adapter Transfer of Self-Supervised Speech Models for Automatic Speech Recognition
Bethan Thomas, Samuel Kessler, Salah Karout
Self-supervised learning (SSL) is a powerful tool that allows learning of underlying representations from unlabeled data. Transformer based models such as wav2vec 2.0 and HuBERT ar…
Fine-grained Multi-Modal Self-Supervised Learning
Duo Wang, Salah Karout
Multi-Modal Self-Supervised Learning from videos has been shown to improve model's performance on various downstream tasks. However, such Self-Supervised pre-training requires larg…
An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning
Samuel Kessler, Bethan Thomas, Salah Karout
We present a method for transferring pre-trained self-supervised (SSL) speech representations to multiple languages. There is an abundance of unannotated speech, so creating self-s…
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
Dario Fuoli, Zhiwu Huang, Shuhang Gu +23
This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR)…