23 citations · 47 across the 11 of their papers we have counts for
4 papers · 1 filter
PrimSeq: a deep learning-based pipeline to quantitate rehabilitation training
Avinash Parnandi, Aakash Kaku, Anita Venkatesan +7
Stroke rehabilitation seeks to increase neuroplasticity through the repeated practice of functional motions, but may have minimal impact on recovery because of insufficient repetit…
Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution
Aakash Kaku, Kangning Liu, Avinash Parnandi +7
Automatic action identification from video and kinematic data is an important machine learning problem with applications ranging from robotics to smart health. Most existing works…
Deep Probability Estimation
Sheng Liu, Aakash Kaku, Weicheng Zhu +8
Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty. Probability-estimation models are trained…
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning
Aakash Kaku, Sahana Upadhya, Narges Razavian
We show that bringing intermediate layers' representations of two augmented versions of an image closer together in self-supervised learning helps to improve the momentum contrasti…