18 citations · 27 across the 8 of their papers we have counts for
4 papers · 1 filter
FairNVT: Fair Classification via Noise Injection in Vision Transformers
Qiaoyue Tang, Sepidehsadat Hosseini, Mengyao Zhai +2
This paper presents FairNVT, a lightweight debiasing framework for pretrained transformer-based encoders that improves prediction fairness while preserving task performance. FairNV…
Training a Vision Transformer from scratch in less than 24 hours with 1 GPU
Saghar Irandoust, Thibaut Durand, Yunduz Rakhmangulova +2
Transformers have become central to recent advances in computer vision. However, training a vision Transformer (ViT) model from scratch can be resource intensive and time consuming…
A Variational Auto-Encoder Model for Stochastic Point Processes
Nazanin Mehrasa, Akash Abdu Jyothi, Thibaut Durand +3
We propose a novel probabilistic generative model for action sequences. The model is termed the Action Point Process VAE (APP-VAE), a variational auto-encoder that can capture the…
Learning a Deep ConvNet for Multi-label Classification with Partial Labels
Thibaut Durand, Nazanin Mehrasa, Greg Mori
Deep ConvNets have shown great performance for single-label image classification (e.g. ImageNet), but it is necessary to move beyond the single-label classification task because pi…