15 citations · 29 across the 10 of their papers we have counts for
4 papers · 1 filter
ActMAD: Activation Matching to Align Distributions for Test-Time-Training
Muhammad Jehanzeb Mirza, Pol Jané Soneira, Wei Lin +3
Test-Time-Training (TTT) is an approach to cope with out-of-distribution (OOD) data by adapting a trained model to distribution shifts occurring at test-time. We propose to perform…
Optimizing DNN Compilation for Distributed Training with Joint OP and Tensor Fusion
Xiaodong Yi, Shiwei Zhang, Lansong Diao +6
This paper proposes DisCo, an automatic deep learning compilation module for data-parallel distributed training. Unlike most deep learning compilers that focus on training or infer…
Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network
Yunzhi Huang, Sahar Ahmad, Luyi Han +6
Missing scans are inevitable in longitudinal studies due to either subject dropouts or failed scans. In this paper, we propose a deep learning framework to predict missing scans fr…
EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing
Chengyu Wang, Minghui Qiu, Chen Shi +7
The success of Pre-Trained Models (PTMs) has reshaped the development of Natural Language Processing (NLP). Yet, it is not easy to obtain high-performing models and deploy them onl…