Vijil Chenthamarakshan

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 47

Top Topics

Iterative Refinement

Molecular Dynamics

Generative Model

Top Venues

Publications

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
Larimar: Large Language Models with Episodic Memory Control. CoRR (2024)
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation. CoRR (2024)
Jerret Ross, Brian Belgodere, Samuel C. Hoffman, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
GP-MoLFormer: A Foundation Model For Molecular Generation. CoRR (2024)
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Structure-Informed Protein Language Model. CoRR (2024)
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. AAAI (2023)
Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
Reprogramming Pretrained Language Models for Antibody Sequence Infilling. ICML (2023)
Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E. Hadfield, Oliver M. Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, Frank von Delft, Charlotte M. Deane
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. J. Chem. Inf. Model. 63 (10) (2023)
Zuobai Zhang, Minghao Xu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Enhancing Protein Language Models with Structure-based Encoder and Pre-training. CoRR (2023)
Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs Campbell, Payel Das, Lav R. Varshney
Efficient Equivariant Transfer Learning from Pretrained Models. NeurIPS (2023)
Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Rose Driggs-Campbell, Payel Das, Lav R. Varshney
Equivariant Few-Shot Learning from Pretrained Models. CoRR (2023)
Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Protein Representation Learning by Geometric Structure Pretraining. ICLR (2023)
Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction. CoRR (2023)
Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction. NeurIPS (2023)
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
Cloud-Based Real-Time Molecular Screening Platform with MolFormer. ECML/PKDD (6) (2022)
Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das
Optimizing molecules using efficient queries from property evaluations. Nat. Mach. Intell. 4 (1) (2022)
N. Joseph Tatro, Payel Das, Pin-Yu Chen, Vijil Chenthamarakshan, Rongjie Lai
Learning Geometrically Disentangled Representations of Protein Folding Simulations. CoRR (2022)
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
Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework. CoRR (2022)
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. CoRR (2022)
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
GT4SD: Generative Toolkit for Scientific Discovery. CoRR (2022)
Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
Reprogramming Large Pretrained Language Models for Antibody Sequence Infilling. CoRR (2022)
Igor Melnyk, Aurélie C. Lozano, Payel Das, Vijil Chenthamarakshan
AlphaFold Distillation for Improved Inverse Protein Folding. CoRR (2022)
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
Cloud-Based Real-Time Molecular Screening Platform with MolFormer. CoRR (2022)
Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
Large-scale chemical language representations capture molecular structure and properties. Nat. Mac. Intell. 4 (12) (2022)
Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP (2022)
Zuobai Zhang, Minghao Xu, Arian R. Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Protein Representation Learning by Geometric Structure Pretraining. CoRR (2022)
Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. CoRR (2021)
Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
Do Large Scale Molecular Language Representations Capture Important Structural Information? CoRR (2021)
Samuel C. Hoffman, Vijil Chenthamarakshan, Dmitry Yu. Zubarev, Daniel P. Sanders, Payel Das
Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model. CoRR (2021)
Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurelie C. Lozano
Benchmarking deep generative models for diverse antibody sequence design. CoRR (2021)
Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR (2021)
Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. ICML (2021)
Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
Learning Implicit Text Generation via Feature Matching. CoRR (2020)
Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick
Explaining Chemical Toxicity using Missing Features. CoRR (2020)
Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
Learning Implicit Text Generation via Feature Matching. ACL (2020)
Vijil Chenthamarakshan, Payel Das, Inkit Padhi, Hendrik Strobelt, Kar Wai Lim, Benjamin Hoover, Samuel C. Hoffman, Aleksandra Mojsilovic
Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. CoRR (2020)
Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. NeurIPS (2020)
Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das
Optimizing Molecules using Efficient Queries from Property Evaluations. CoRR (2020)
Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR (2020)
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
Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics. CoRR (2020)
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
A Sequential Set Generation Method for Predicting Set-Valued Outputs. AAAI (2019)
Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt, Payel Das, Inkit Padhi, Cícero Nogueira dos Santos, Kahini Wadhawan, Vijil Chenthamarakshan
Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection. DGS@ICLR (2019)
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network. IBM J. Res. Dev. 63 (4/5) (2019)
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
A Sequential Set Generation Method for Predicting Set-Valued Outputs. CoRR (2019)
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
Fairness GAN. CoRR (2018)
Payel Das, Kahini Wadhawan, Oscar Chang, Tom Sercu, Cícero Nogueira dos Santos, Matthew Riemer, Inkit Padhi, Vijil Chenthamarakshan, Aleksandra Mojsilovic
PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences. CoRR (2018)
Md. Faisal Mahbub Chowdhury, Vijil Chenthamarakshan, Rishav Chakravarti, Alfio Massimiliano Gliozzo
Query Focused Variable Centroid Vectors for Passage Re-ranking in Semantic Search. CoRR (2018)
Dharmashankar Subramanian, Debarun Bhattacharjya, Ruben Rodriguez Torrado, Jeffrey O. Kephart, Vijil Chenthamarakshan, Jesus Rios
A cognitive assistant for risk identification and modeling. IEEE BigData (2017)
Vijil Chenthamarakshan, Prasad M. Deshpande, Raghu Krishnapuram, Ramakrishna Varadarajan, Knut Stolze
WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction. CoRR (2015)
Kush R. Varshney, Vijil Chenthamarakshan, Scott W. Fancher, Jun Wang, DongPing Fang, Aleksandra Mojsilovic
Predicting employee expertise for talent management in the enterprise. KDD (2014)
Prem Melville, Vijil Chenthamarakshan, Richard D. Lawrence, James Powell, Moses Mugisha, Sharad Sapra, Rajesh Anandan, Solomon Assefa
Amplifying the voice of youth in Africa via text analytics. KDD (2013)
Vijil Chenthamarakshan, Ramakrishna Varadarajan, Prasad M. Deshpande, Raghuram Krishnapuram, Knut Stolze
WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction. WAIM (2012)
Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani, Richard D. Lawrence
Concept Labeling: Building Text Classifiers with Minimal Supervision. IJCAI (2011)
Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan
Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. AAAI (2011)
Vijil Chenthamarakshan, Rafah Hosn, Shajith Ikbal, Nandakishore Kambhatla, Debapriyo Majumdar, Soumitra Sarkar
Measuring Compliance and Deviations in a Template-Based Service Contract Development Process. IEEE SCC (2010)
Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan
ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. ICDM Workshops (2010)
Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla
Urdu and Hindi: Translation and sharing of linguistic resources. COLING (Posters) (2010)
Karthik Visweswariah, Jirí Navrátil, Jeffrey S. Sorensen, Vijil Chenthamarakshan, Nandakishore Kambhatla
Syntax Based Reordering with Automatically Derived Rules for Improved Statistical Machine Translation. COLING (2010)
Amit Singh, Rose Catherine, Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla
PROSPECT: a system for screening candidates for recruitment. CIKM (2010)
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
Effective decision support systems for workforce deployment. IBM J. Res. Dev. 54 (6) (2010)
Rema Ananthanarayanan, Vijil Chenthamarakshan, Heng Chu, Prasad M. Deshpande, Raghu Krishnapuram, Shajeer K. Mohammed
Dependency Analysis Framework for Software Service Delivery. IEEE SCC (2009)
Vijil Chenthamarakshan, Kuntal Dey, Jianying Hu, Aleksandra Mojsilovic, W. Riddle, Vikas Sindhwani
Leveraging social networks for corporate staffing and expert recommendation. IBM J. Res. Dev. 53 (6) (2009)
Rema Ananthanarayanan, Vijil Chenthamarakshan, Prasad M. Deshpande, Raghuram Krishnapuram
Rule based synonyms for entity extraction from noisy text. AND (2008)