Search Results for author: Neeraj Kumar

Found 39 papers, 9 papers with code

CACTUS: Chemistry Agent Connecting Tool-Usage to Science

1 code implementation2 May 2024 Andrew D. McNaughton, Gautham Ramalaxmi, Agustin Kruel, Carter R. Knutson, Rohith A. Varikoti, Neeraj Kumar

We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama2-7b, and Mistral-7b, on a benchmark of thousands of chemistry questions.

Molecular Property Prediction Prompt Engineering +1

Style Description based Text-to-Speech with Conditional Prosodic Layer Normalization based Diffusion GAN

no code implementations27 Oct 2023 Neeraj Kumar, Ankur Narang, Brejesh lall

In this paper, we present a Diffusion GAN based approach (Prosodic Diff-TTS) to generate the corresponding high-fidelity speech based on the style description and content text as an input to generate speech samples within only 4 denoising steps.

Decoder Denoising

Distraction-free Embeddings for Robust VQA

no code implementations31 Aug 2023 Atharvan Dogra, Deeksha Varshney, Ashwin Kalyan, Ameet Deshpande, Neeraj Kumar

The generation of effective latent representations and their subsequent refinement to incorporate precise information is an essential prerequisite for Vision-Language Understanding (VLU) tasks such as Video Question Answering (VQA).

Question Answering Video Question Answering +1

An Effective Meaningful Way to Evaluate Survival Models

1 code implementation1 Jun 2023 Shi-ang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner

One straightforward metric to evaluate a survival prediction model is based on the Mean Absolute Error (MAE) -- the average of the absolute difference between the time predicted by the model and the true event time, over all subjects.

Survival Prediction

KL Regularized Normalization Framework for Low Resource Tasks

no code implementations21 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.

Dynamic Molecular Graph-based Implementation for Biophysical Properties Prediction

no code implementations20 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.

Time Series Time Series Analysis

Scaffold-Based Multi-Objective Drug Candidate Optimization

no code implementations15 Dec 2022 Agustin Kruel, Andrew D. McNaughton, Neeraj Kumar

In therapeutic design, balancing various physiochemical properties is crucial for molecule development, similar to how Multiparameter Optimization (MPO) evaluates multiple variables to meet a primary goal.

Diversity

An Overview of Violence Detection Techniques: Current Challenges and Future Directions

no code implementations21 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.

Activity Recognition

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

1 code implementation22 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.

Boundary Detection Federated Learning

EEG based Emotion Recognition: A Tutorial and Review

no code implementations16 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.

EEG Emotion Recognition

Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm

no code implementations3 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.

Attribute Management +1

Space-Air-Ground Integrated Multi-domain Network Resource Orchestration based on Virtual Network Architecture: a DRL Method

no code implementations3 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.

Network Embedding

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks

1 code implementation30 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.

Explainable artificial intelligence Graph Neural Network

Few Shot Activity Recognition Using Variational Inference

no code implementations20 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.

Action Recognition Few-Shot Learning +2

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

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.

Drug Discovery Graph Attention

FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia

no code implementations26 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.

Federated Learning Generative Adversarial Network

One Shot Audio to Animated Video Generation

no code implementations19 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.

Video Generation

Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective

no code implementations10 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.

Multi Modal Adaptive Normalization for Audio to Video Generation

no code implementations14 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.

Optical Flow Estimation SSIM +1

Few Shot Adaptive Normalization Driven Multi-Speaker Speech Synthesis

no code implementations14 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.

Cultural Vocal Bursts Intensity Prediction Speech Synthesis

Robust One Shot Audio to Video Generation

no code implementations14 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.

Generative Adversarial Network Marketing +3

Mitigating the Impact of Adversarial Attacks in Very Deep Networks

no code implementations8 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.

Data Poisoning

Phase transitions in D-dimensional Gauss-Bonnet-Born-Infeld AdS black holes

no code implementations9 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

Blockchain based Attack Detection on Machine Learning Algorithms for IoT based E-Health Applications

no code implementations3 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.

BIG-bench Machine Learning

Efficient Power-Splitting and Resource Allocation for Cellular V2X Communications

no code implementations14 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.

Systematically designing better instance counting models on cell images with Neural Arithmetic Logic Units

1 code implementation14 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.

Data Augmentation regression

A Provably Secure and Efficient Identity-Based Anonymous Authentication Scheme for Mobile Edge Computing

no code implementations22 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.

Cloud Computing Edge-computing

Deep Learning-Based Image Kernel for Inductive Transfer

no code implementations13 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.

Transfer Learning

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