Vijil Chenthamarakshan

According to our database, Vijil Chenthamarakshan authored at least 51 papers between 2008 and 2024.

Collaborative distances:

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

2024

Larimar: Large Language Models with Episodic Memory Control.

Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarath Swaminathan, Sihui Dai, Aurélie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jirí Navrátil, Soham Dan, Pin-Yu Chen

CoRR, 2024

ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation.

Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang

CoRR, 2024

Structure-Informed Protein Language Model.

Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang

CoRR, 2024

2023

Equivariant Few-Shot Learning from Pretrained Models.

Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Rose Driggs-Campbell, Payel Das, Lav R. Varshney

CoRR, 2023

Enhancing Protein Language Models with Structure-based Encoder and Pre-training.

Zuobai Zhang, Minghao Xu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang

CoRR, 2023

Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction.

Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

CoRR, 2023

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction.

Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Equivariant Transfer Learning from Pretrained Models.

Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs Campbell, Payel Das, Lav R. Varshney

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reprogramming Pretrained Language Models for Antibody Sequence Infilling.

Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das

Proceedings of the International Conference on Machine Learning, 2023

Protein Representation Learning by Geometric Structure Pretraining.

Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models.

Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Large-scale chemical language representations capture molecular structure and properties.

Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das

Nat. Mac. Intell., December, 2022

Optimizing molecules using efficient queries from property evaluations.

Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das

Nat. Mach. Intell., 2022

Reprogramming Large Pretrained Language Models for Antibody Sequence Infilling.

Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das

CoRR, 2022

AlphaFold Distillation for Improved Inverse Protein Folding.

Igor Melnyk, Aurélie C. Lozano, Payel Das, Vijil Chenthamarakshan

CoRR, 2022

GT4SD: Generative Toolkit for Scientific Discovery.

Matteo Manica, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Jannis Born, Dean Clarke, Yves Gaetan Nana Teukam, Samuel C. Hoffman, Matthew Buchan, Vijil Chenthamarakshan, Timothy Donovan, Hsiang-Han Hsu, Federico Zipoli, Oliver Schilter, Giorgio Giannone, Akihiro Kishimoto, Lisa Hamada, Inkit Padhi, Karl Wehden, Lauren McHugh, Alexy Khrabrov, Payel Das, Seiji Takeda, John R. Smith

CoRR, 2022

Learning Geometrically Disentangled Representations of Protein Folding Simulations.

N. Joseph Tatro, Payel Das, Pin-Yu Chen, Vijil Chenthamarakshan, Rongjie Lai

CoRR, 2022

Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework.

Vijil Chenthamarakshan, Samuel C. Hoffman, C. David Owen, Petra Lukacik, Claire Strain-Damerell, Daren Fearon, Tika R. Malla, Anthony Tumber, Christopher J. Schofield, Helen M. E. Duyvesteyn, Wanwisa Dejnirattisai, Loic Carrique, Thomas S. Walter, Gavin R. Screaton, Tetiana Matviiuk, Aleksandra Mojsilovic, Jason Crain, Martin A. Walsh, David I. Stuart, Payel Das

CoRR, 2022

Cloud-Based Real-Time Molecular Screening Platform with MolFormer.

Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations.

Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model.

Samuel C. Hoffman, Vijil Chenthamarakshan, Dmitry Yu. Zubarev, Daniel P. Sanders, Payel Das

CoRR, 2021

Benchmarking deep generative models for diverse antibody sequence design.

Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurélie C. Lozano

CoRR, 2021

Do Large Scale Molecular Language Representations Capture Important Structural Information?

Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das

CoRR, 2021

Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design.

Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics.

Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das

CoRR, 2020

Explaining Chemical Toxicity using Missing Features.

Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick

CoRR, 2020

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics.

Payel Das, Tom Sercu, Kahini Wadhawan, Inkit Padhi, Sebastian Gehrmann, Flaviu S. Cipcigan, Vijil Chenthamarakshan, Hendrik Strobelt, Cícero Nogueira dos Santos, Pin-Yu Chen, Yi Yan Yang, Jeremy Tan, James Hedrick, Jason Crain, Aleksandra Mojsilovic

CoRR, 2020

Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models.

Vijil Chenthamarakshan, Payel Das, Inkit Padhi, Hendrik Strobelt, Kar Wai Lim, Benjamin Hoover, Samuel C. Hoffman, Aleksandra Mojsilovic

CoRR, 2020

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models.

Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Implicit Text Generation via Feature Matching.

Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Fairness GAN: Generating datasets with fairness properties using a generative adversarial network.

Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney

IBM J. Res. Dev., 2019

Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection.

Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt, Payel Das, Inkit Padhi, Cícero Nogueira dos Santos, Kahini Wadhawan, Vijil Chenthamarakshan

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

A Sequential Set Generation Method for Predicting Set-Valued Outputs.

Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences.

Payel Das, Kahini Wadhawan, Oscar Chang, Tom Sercu, Cícero Nogueira dos Santos, Matthew Riemer, Inkit Padhi, Vijil Chenthamarakshan, Aleksandra Mojsilovic

CoRR, 2018

Fairness GAN.

Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney

CoRR, 2018

Query Focused Variable Centroid Vectors for Passage Re-ranking in Semantic Search.

Md. Faisal Mahbub Chowdhury, Vijil Chenthamarakshan, Rishav Chakravarti, Alfio Massimiliano Gliozzo

CoRR, 2018

2017

A cognitive assistant for risk identification and modeling.

Dharmashankar Subramanian, Debarun Bhattacharjya, Ruben Rodriguez Torrado, Jeffrey O. Kephart, Vijil Chenthamarakshan, Jesus Rios

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2014

Predicting employee expertise for talent management in the enterprise.

Kush R. Varshney, Vijil Chenthamarakshan, Scott W. Fancher, Jun Wang, DongPing Fang, Aleksandra Mojsilovic

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Amplifying the voice of youth in Africa via text analytics.

Prem Melville, Vijil Chenthamarakshan, Richard D. Lawrence, James Powell, Moses Mugisha, Sharad Sapra, Rajesh Anandan, Solomon Assefa

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012

WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction.

Vijil Chenthamarakshan, Ramakrishna Varadarajan, Prasad M. Deshpande, Raghuram Krishnapuram, Knut Stolze

Proceedings of the Web-Age Information Management - 13th International Conference, 2012

2011

Concept Labeling: Building Text Classifiers with Minimal Supervision.

Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani, Richard D. Lawrence

Proceedings of the IJCAI 2011, 2011

Transfer Latent Semantic Learning: Microblog Mining with Less Supervision.

Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Effective decision support systems for workforce deployment.

Vijil Chenthamarakshan, Kashyap Dixit, M. Gattani, Munish Goyal, Pranav Gupta, Nanda Kambhatla, Rohit Lotlikar, Debapriyo Majumdar, Gyana R. Parija, Sambuddha Roy, Soujanya Soni, Karthik Visweswariah

IBM J. Res. Dev., 2010

ALPOS: A Machine Learning Approach for Analyzing Microblogging Data.

Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan

Proceedings of the ICDMW 2010, 2010

Syntax Based Reordering with Automatically Derived Rules for Improved Statistical Machine Translation.

Karthik Visweswariah, Jirí Navrátil, Jeffrey S. Sorensen, Vijil Chenthamarakshan, Nandakishore Kambhatla

Proceedings of the COLING 2010, 2010

Urdu and Hindi: Translation and sharing of linguistic resources.

Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla

Proceedings of the COLING 2010, 2010

PROSPECT: a system for screening candidates for recruitment.

Amit Singh, Rose Catherine, Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla

Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

Measuring Compliance and Deviations in a Template-Based Service Contract Development Process.

Vijil Chenthamarakshan, Rafah Hosn, Shajith Ikbal, Nandakishore Kambhatla, Debapriyo Majumdar, Soumitra Sarkar

Proceedings of the 2010 IEEE International Conference on Services Computing, 2010

2009

Leveraging social networks for corporate staffing and expert recommendation.

Vijil Chenthamarakshan, Kuntal Dey, Jianying Hu, Aleksandra Mojsilovic, W. Riddle, Vikas Sindhwani

IBM J. Res. Dev., 2009

Dependency Analysis Framework for Software Service Delivery.

Rema Ananthanarayanan, Vijil Chenthamarakshan, Heng Chu, Prasad M. Deshpande, Raghu Krishnapuram, Shajeer K. Mohammed

Proceedings of the 2009 IEEE International Conference on Services Computing (SCC 2009), 2009

2008

Rule based synonyms for entity extraction from noisy text.

Rema Ananthanarayanan, Vijil Chenthamarakshan, Prasad M. Deshpande, Raghuram Krishnapuram

Proceedings of the Second Workshop on Analytics for Noisy Unstructured Text Data, 2008