no code implementations • 21 Dec 2022 • Neeraj Kumar, Ankur Narang, Brejesh lall
A lot of normalization techniques have been proposed but the success of normalization in low resource downstream NLP and speech tasks is limited.
no code implementations • 20 Dec 2022 • Carter Knutson, Gihan Panapitiya, Rohith Varikoti, Neeraj Kumar
Neural Networks (GNNs) have revolutionized the molecular discovery to understand patterns and identify unknown features that can aid in predicting biophysical properties and protein-ligand interactions.
no code implementations • 15 Dec 2022 • Agustin Kruel, Andrew McNaughton, Neeraj Kumar
This framework trains itself on-the-fly with the MPO score of each iteration of molecules, and is able to work on a greater number of properties and sample the chemical space around a starting scaffold.
no code implementations • 21 Sep 2022 • Nadia Mumtaz, Naveed Ejaz, Shabana Habib, Syed Muhammad Mohsin, Prayag Tiwari, Shahab S. Band, Neeraj Kumar
The Big Video Data generated in today's smart cities has raised concerns from its purposeful usage perspective, where surveillance cameras, among many others are the most prominent resources to contribute to the huge volumes of data, making its automated analysis a difficult task in terms of computation and preciseness.
no code implementations • 21 May 2022 • Andrew D. McNaughton, Mridula S. Bontha, Carter R. Knutson, Jenna A. Pope, Neeraj Kumar
Efficient design and discovery of target-driven molecules is a critical step in facilitating lead optimization in drug discovery.
1 code implementation • 22 Apr 2022 • Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-han Wang, G Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y Huang, Ken Chang, Carmen Balana, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S Alexander, Joseph Lombardo, Joshua D Palmer, Adam E Flanders, Adam P Dicker, Haris I Sair, Craig K Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A Vogelbaum, J Ross Mitchell, Joaquim Farinhas, Joseph A Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C Pinho, Divya Reddy, James Holcomb, Benjamin C Wagner, Benjamin M Ellingson, Timothy F Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B Martins, Bernardo C A Teixeira, Flávia Sprenger, David Menotti, Diego R Lucio, Pamela Lamontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W Lui, Richard McKinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E Sloan, Vachan Vadmal, Kristin Waite, Rivka R Colen, Linmin Pei, Murat AK, Ashok Srinivasan, J Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V M Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R van der Voort, Ahmed Alafandi, Fatih Incekara, Maarten MJ Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W Schouten, Hendrikus J Dubbink, Arnaud JPE Vincent, Martin J van den Bent, Pim J French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B Chambless, Akshitkumar Mistry, Reid C Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G H Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A Velastin, Godwin Ogbole, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu'aibu, Adeleye Dorcas, Mayowa Soneye, Farouk Dako, Amber L Simpson, Mohammad Hamghalam, Jacob J Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y Moraes, Michael A Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S Barnholtz-Sloan, Jason Martin, Spyridon Bakas
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data.
no code implementations • 16 Mar 2022 • Xiang Li, Yazhou Zhang, Prayag Tiwari, Dawei Song, Bin Hu, Meihong Yang, Zhigang Zhao, Neeraj Kumar, Pekka Marttinen
Hence, in this paper, we review from the perspective of researchers who try to take the first step on this topic.
no code implementations • 7 Feb 2022 • Peiying Zhang, Xue Pang, Neeraj Kumar, Gagangeet Singh Aujla, Haotong Cao
With the advent of the Internet of things (IoT) era, more and more devices are connected to the IoT.
no code implementations • 3 Feb 2022 • Peiying Zhang, Chao Wang, Gagangeet Singh Aujla, Neeraj Kumar, Mohsen Guizani
This paper proposes a bandwidth aware multi domain virtual network embedding algorithm (BA-VNE).
no code implementations • 3 Feb 2022 • Peiying Zhang, Chao Wang, Neeraj Kumar, Lei Liu
Based on virtual network architecture and deep reinforcement learning (DRL), we model SAGIN's heterogeneous resource orchestration as a multi-domain virtual network embedding (VNE) problem, and propose a SAGIN cross-domain VNE algorithm.
no code implementations • 3 Feb 2022 • Peiying Zhang, Chao Wang, Neeraj Kumar, Weishan Zhang, Lei Liu
Simulation experiments verified that the dynamic VNE algorithm based on RL and GCNN has good basic VNE characteristics.
no code implementations • 3 Feb 2022 • Peiying Zhang, Chao Wang, Chunxiao Jiang, Neeraj Kumar, Qinghua Lu
Based on the above two problems faced by ICPSs, we propose a virtual network embedded (VNE) algorithm with computing, storage resources and security constraints to ensure the rationality and security of resource allocation in ICPSs.
1 code implementation • 30 Nov 2021 • Carter Knutson, Mridula Bontha, Jenna A. Bilbrey, Neeraj Kumar
These models are further adapted for regression tasks to predict experimental binding affinities and pIC50 is crucial for drugs potency and efficacy.
no code implementations • 27 Nov 2021 • Luca Pion-Tonachini, Kristofer Bouchard, Hector Garcia Martin, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus Zwart, Neeraj Kumar, Amy Justice, Claire Tomlin, Daniel Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Ken Kreutz-Delgado, Michael W. Mahoney, James B. Brown
We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery.
no code implementations • 20 Aug 2021 • Neeraj Kumar, Siddhansh Narang
To the best of our knowledge, we are the first to explore variational inference along with householder transformations to capture the full rank covariance matrix of posterior distribution, for few shot learning in activity recognition.
4 code implementations • ICLR 2022 • Yulun Wu, Mikaela Cashman, Nicholas Choma, Érica T. Prates, Verónica G. Melesse Vergara, Manesh Shah, Andrew Chen, Austin Clyde, Thomas S. Brettin, Wibe A. de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown
We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain.
no code implementations • 25 May 2021 • Waqas Ahmed, Amir Rasool, Neeraj Kumar, Abdul RehmanJaved, Thippa Reddy Gadekallu, Zunera Jalil, Natalia Kryvinska
The usage of mobile phones is pretty ordinary in this present era.
1 code implementation • 7 May 2021 • Jenna Bilbrey, Logan Ward, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman
We examine a pair of graph generative models for the therapeutic design of novel drug candidates targeting SARS-CoV-2 viral proteins.
no code implementations • 26 Apr 2021 • Longling Zhang, Bochen Shen, Ahmed Barnawi, Shan Xi, Neeraj Kumar, Yi Wu
Under the FL framework and Differentially Private thinking, we propose a FederatedDifferentially Private Generative Adversarial Network (FedDPGAN) to detectCOVID-19 pneumonia for sustainable smart cities.
no code implementations • 19 Feb 2021 • Neeraj Kumar, Srishti Goel, Ankur Narang, Brejesh lall, Mujtaba Hasan, Pranshu Agarwal, Dipankar Sarkar
We propose a novel method OneShotAu2AV to generate an animated video of arbitrary length using an audio clip and a single unseen image of a person as an input.
no code implementations • 10 Feb 2021 • Rajendra P. Joshi, Neeraj Kumar
Domain-aware machine learning (ML) models have been increasingly adopted for accelerating small molecule therapeutic design in the recent years.
1 code implementation • 9 Feb 2021 • Logan Ward, Jenna A. Bilbrey, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman
Design of new drug compounds with target properties is a key area of research in generative modeling.
no code implementations • 14 Dec 2020 • Neeraj Kumar, Srishti Goel, Ankur Narang, Brejesh lall
The multi-modal adaptive normalization uses the various features of audio and video such as Mel spectrogram, pitch, energy from audio signals and predicted keypoint heatmap/optical flow and a single image to learn the respective affine parameters to generate highly expressive video.
no code implementations • 14 Dec 2020 • Neeraj Kumar, Srishti Goel, Ankur Narang, Mujtaba Hasan
High-quality video generation with expressive facial movements is a challenging problem that involves complex learning steps for generative adversarial networks.
no code implementations • 14 Dec 2020 • Neeraj Kumar, Srishti Goel, Ankur Narang, Brejesh lall
High quality multi-speaker speech synthesis while considering prosody and in a few shot manner is an area of active research with many real-world applications.
no code implementations • 8 Dec 2020 • Mohammed Hassanin, Ibrahim Radwan, Nour Moustafa, Murat Tahtali, Neeraj Kumar
In it, a Defensive Feature Layer (DFL) is integrated with a well-known DNN architecture which assists in neutralizing the effects of illegitimate perturbation samples in the feature space.
no code implementations • 9 Nov 2020 • Neeraj Kumar, Sunandan Gangopadhyay
In this paper, we have investigated the phase transition in black holes when Gauss-Bonnet corrections to the spacetime curvature and Born-Infeld extension in stress-energy tensor of electromagnetic field are considered in a negative cosmological constant background.
General Relativity and Quantum Cosmology
no code implementations • 3 Nov 2020 • Thippa Reddy Gadekallu, Manoj M K, Sivarama Krishnan S, Neeraj Kumar, Saqib Hakak, Sweta Bhattacharya
Hence, in this article, we have proposed blockchain based solution to secure the datasets generated from IoT devices for E-Health applications.
no code implementations • 14 Jul 2020 • Furqan Jameel, Wali Ullah Khan, Neeraj Kumar, Riku Jantti
This article aims to further push the state-of-the-art of cellular V2X communications by providing an optimization framework for wireless charging, power allocation, and resource block assignment.
1 code implementation • 14 Apr 2020 • Ashish Rana, Taranveer Singh, Harpreet Singh, Neeraj Kumar, Prashant Singh Rana
These numerically biased units are added in the form of residual concatenated layers to original architectures and a comparative experimental study is done with these newly proposed changes.
no code implementations • 19 Mar 2020 • Hrushikesh Loya, Pranav Poduval, Deepak Anand, Neeraj Kumar, Amit Sethi
Survival models are used in various fields, such as the development of cancer treatment protocols.
no code implementations • 22 Feb 2019 • Xiaoying Jia，Debiao He, Neeraj Kumar, and Kim-Kwang Raymond Choo, Senior Member, IEEE
Mobile edge computing (MEC) allows one to overcome a number of limitations inherent in cloud computing, although achieving the broad range of security requirements in MEC settings remains challenging.
no code implementations • 17 Sep 2018 • Deepa K, Radhamani G, Vinod P, Mohammad Shojafar, Neeraj Kumar, Mauro Conti
Ever increasing number of Android malware, has always been a concern for cybersecurity professionals.
no code implementations • 13 Dec 2015 • Neeraj Kumar, Animesh Karmakar, Ranti Dev Sharma, Abhinav Mittal, Amit Sethi
We propose a method to classify images from target classes with a small number of training examples based on transfer learning from non-target classes.