Aakash Kaku

According to our database, Aakash Kaku authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Quantifying Impairment and Disease Severity Using AI Models Trained on Healthy Subjects.

Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda

CoRR, 2023

2022

StrokeRehab: A Benchmark Dataset for Sub-second Action Identification.

Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep Probability Estimation.

Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda

Proceedings of the International Conference on Machine Learning, 2022

2021

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras

npj Digit. Medicine, 2021

PrimSeq: a deep learning-based pipeline to quantitate rehabilitation training.

Avinash Parnandi, Aakash Kaku, Anita Venkatesan, Natasha Pandit, Audre Wirtanen, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Dawn Nilsen, Carlos Fernandez-Granda, Heidi M. Schambra

CoRR, 2021

Deep Probability Estimation.

Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Laure Zanna, Narges Razavian, Carlos Fernandez-Granda

CoRR, 2021

Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution.

Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda

CoRR, 2021

Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning.

Aakash Kaku, Sahana Upadhya, Narges Razavian

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras

CoRR, 2020

Be Like Water: Robustness to Extraneous Variables Via Adaptive Feature Normalization.

Aakash Kaku, Sreyas Mohan, Avinash Parnandi, Heidi M. Schambra, Carlos Fernandez-Granda

CoRR, 2020

Towards data-driven stroke rehabilitation via wearable sensors and deep learning.

Aakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda

Proceedings of the Machine Learning for Healthcare Conference, 2020

2019

Knee Cartilage Segmentation Using Diffusion-Weighted MRI.

Alejandra Duarte, Chaitra V. Hegde, Aakash Kaku, Sreyas Mohan, José G. Raya

CoRR, 2019

DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation.

Aakash Kaku, Chaitra V. Hegde, Jeffrey Huang, Sohae Chung, Xiuyuan Wang, Matthew Young, Alireza Radmanesh, Yvonne W. Lui, Narges Razavian

CoRR, 2019