Search Results for author: Kushal Shah

Found 8 papers, 1 papers with code

Enhancing Grammatical Error Detection using BERT with Cleaned Lang-8 Dataset

1 code implementation23 Nov 2024 Rahul Nihalani, Kushal Shah

Traditional rule-based systems have an F1 score of 0. 50-0. 60 and earlier machine learning models give an F1 score of 0. 65-0. 75, including decision trees and simple neural networks.

Grammatical Error Detection

BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery

no code implementations15 Nov 2024 Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Kucukbenli, Saee Paliwal, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B Costa

We introduce the BioNeMo Framework to facilitate the training of computational biology and chemistry AI models across hundreds of GPUs.

Drug Discovery

Malaria detection from RBC images using shallow Convolutional Neural Networks

no code implementations22 Oct 2020 Subrata Sarkar, Rati Sharma, Kushal Shah

The advent of Deep Learning models like VGG-16 and Resnet-50 has considerably revolutionized the field of image classification, and by using these Convolutional Neural Networks (CNN) architectures, one can get a high classification accuracy on a wide variety of image datasets.

Classification General Classification +1

A Simple Approach to Classify Fictional and Non-Fictional Genres

no code implementations WS 2019 Mohammed Rameez Qureshi, Sidharth Ranjan, Rajakrishnan Rajkumar, Kushal Shah

In this work, we deploy a logistic regression classifier to ascertain whether a given document belongs to the fiction or non-fiction genre.

feature selection Sentence

Open-endedness in AI systems, cellular evolution and intellectual discussions

no code implementations28 Dec 2018 Kushal Shah

One of the biggest challenges that artificial intelligence (AI) research is facing in recent times is to develop algorithms and systems that are not only good at performing a specific intelligent task but also good at learning a very diverse of skills somewhat like humans do.

Description Logics based Formalization of Wh-Queries

no code implementations25 Dec 2013 Sourish Dasgupta, Rupali KaPatel, Ankur Padia, Kushal Shah

The problem of Natural Language Query Formalization (NLQF) is to translate a given user query in natural language (NL) into a formal language so that the semantic interpretation has equivalence with the NL interpretation.

Information Retrieval Question Answering +2

Formal Ontology Learning on Factual IS-A Corpus in English using Description Logics

no code implementations25 Dec 2013 Sourish Dasgupta, Ankur Padia, Kushal Shah, Prasenjit Majumder

Hence, we also claim that such sentences requires special studies in the context of OL before any truly formal OL can be proposed.

DLOLIS-A: Description Logic based Text Ontology Learning

no code implementations24 Mar 2013 Sourish Dasgupta, Ankur Padia, Kushal Shah, Rupali KaPatel, Prasenjit Majumder

Researchers in this field have been motivated by the possibility of automatically building a knowledge base on top of text documents so as to support reasoning based knowledge extraction.

Formal Logic

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