Rule based synonyms for entity extraction from noisy text. - Rema Ananthanarayanan; Vijil Chenthamarakshan; Prasad M. Deshpande; Raghuram Krishnapuram (AND, 2008)

Dependency Analysis Framework for Software Service Delivery. - Rema Ananthanarayanan; Vijil Chenthamarakshan; Heng Chu; Prasad M. Deshpande; Raghu Krishnapuram; Shajeer K. Mohammed (IEEE SCC, 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)

Measuring Compliance and Deviations in a Template-Based Service Contract Development Process. - Vijil Chenthamarakshan; Rafah Hosn; Shajith Ikbal; Nandakishore Kambhatla; Debapriyo Majumdar; Soumitra Sarkar (IEEE SCC, 2010)

PROSPECT: a system for screening candidates for recruitment. - Amit Singh 003; Rose Catherine; Karthik Visweswariah; Vijil Chenthamarakshan; Nandakishore Kambhatla (CIKM, 2010)

Urdu and Hindi: Translation and sharing of linguistic resources. - Karthik Visweswariah; Vijil Chenthamarakshan; Nandakishore Kambhatla (COLING (Posters), 2010)

Syntax Based Reordering with Automatically Derived Rules for Improved Statistical Machine Translation. - Karthik Visweswariah; Jirí Navrátil 001; Jeffrey S. Sorensen; Vijil Chenthamarakshan; Nandakishore Kambhatla (COLING, 2010)

ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. - Dan Zhang 007; Yan Liu 002; Richard D. Lawrence; Vijil Chenthamarakshan (ICDM Workshops, 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)

Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. - Dan Zhang 007; Yan Liu 002; Richard D. Lawrence; Vijil Chenthamarakshan (AAAI, 2011)

Concept Labeling: Building Text Classifiers with Minimal Supervision. - Vijil Chenthamarakshan; Prem Melville; Vikas Sindhwani; Richard D. Lawrence (IJCAI, 2011)

WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction. - Vijil Chenthamarakshan; Ramakrishna Varadarajan; Prasad M. Deshpande; Raghuram Krishnapuram; Knut Stolze (WAIM, 2012)

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 (KDD, 2013)

Predicting employee expertise for talent management in the enterprise. - Kush R. Varshney; Vijil Chenthamarakshan; Scott W. Fancher; Jun Wang 006; DongPing Fang 001; Aleksandra Mojsilovic (KDD, 2014)

A cognitive assistant for risk identification and modeling. - Dharmashankar Subramanian; Debarun Bhattacharjya; Ruben Rodriguez Torrado; Jeffrey O. Kephart; Vijil Chenthamarakshan; Jesus Rios (IEEE BigData, 2017)

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)

Fairness GAN. - Prasanna Sattigeri; Samuel C. Hoffman; Vijil Chenthamarakshan; Kush R. Varshney (CoRR, 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)

A Sequential Set Generation Method for Predicting Set-Valued Outputs. - Tian Gao; Jie Chen 007; Vijil Chenthamarakshan; Michael Witbrock (AAAI, 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 (DGS@ICLR, 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)

Learning Implicit Text Generation via Feature Matching. - Inkit Padhi; Pierre L. Dognin; Ke Bai; Cícero Nogueira dos Santos; Vijil Chenthamarakshan; Youssef Mroueh; Payel Das (ACL, 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 (NeurIPS, 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)

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; et al. (CoRR, 2020)

Explaining Chemical Toxicity using Missing Features. - Kar Wai Lim; Bhanushee Sharma; Payel Das; Vijil Chenthamarakshan; Jonathan S. Dordick (CoRR, 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)

Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. - Yue Cao 010; Payel Das; Vijil Chenthamarakshan; Pin-Yu Chen; Igor Melnyk; Yang Shen 001 (ICML, 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)

Benchmarking deep generative models for diverse antibody sequence design. - Igor Melnyk; Payel Das; Vijil Chenthamarakshan; Aurélie C. Lozano (CoRR, 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 002; Payel Das (CoRR, 2021)

Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. - Yair Schiff; Vijil Chenthamarakshan; Samuel C. Hoffman; Karthikeyan Natesan Ramamurthy; Payel Das (ICASSP, 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 (ECML/PKDD (6), 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; et al. (CoRR, 2022)

Learning Geometrically Disentangled Representations of Protein Folding Simulations. - N. Joseph Tatro; Payel Das; Pin-Yu Chen; Vijil Chenthamarakshan; Rongjie Lai (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; et al. (CoRR, 2022)

AlphaFold Distillation for Improved Inverse Protein Folding. - Igor Melnyk; Aurélie C. Lozano; Payel Das; Vijil Chenthamarakshan (CoRR, 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)

Optimizing molecules using efficient queries from property evaluations. - Samuel C. Hoffman; Vijil Chenthamarakshan; Kahini Wadhawan; Pin-Yu Chen; Payel Das (Nat. Mach. Intell., 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., 2022)

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 (AAAI, 2023)

Protein Representation Learning by Geometric Structure Pretraining. - Zuobai Zhang; Minghao Xu; Arian Rokkum Jamasb; Vijil Chenthamarakshan; Aurélie C. Lozano; Payel Das; Jian Tang 005 (ICLR, 2023)

Reprogramming Pretrained Language Models for Antibody Sequence Infilling. - Igor Melnyk; Vijil Chenthamarakshan; Pin-Yu Chen; Payel Das; Amit Dhurandhar; Inkit Padhi; Devleena Das (ICML, 2023)

Efficient Equivariant Transfer Learning from Pretrained Models. - Sourya Basu; Pulkit Katdare; Prasanna Sattigeri; Vijil Chenthamarakshan; Katherine Driggs-Campbell; Payel Das; Lav R. Varshney (NeurIPS, 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 005 (NeurIPS, 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 005 (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 005 (CoRR, 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)

A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. - 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 (J. Chem. Inf. Model., 2023)

Larimar: Large Language Models with Episodic Memory Control. - Payel Das; Subhajit Chaudhury; Elliot Nelson; Igor Melnyk; Sarathkrishna Swaminathan; Sihui Dai; Aurélie C. Lozano; Georgios Kollias; Vijil Chenthamarakshan; Jirí Navrátil 001; Soham Dan; Pin-Yu Chen (ICML, 2024)

Multi-Scale Representation Learning for Protein Fitness Prediction. - Zuobai Zhang; Pascal Notin; Yining Huang; Aurélie C. Lozano; Vijil Chenthamarakshan; Debora S. Marks; Payel Das; Jian Tang 005 (NeurIPS, 2024)

Structure-Informed Protein Language Model. - Zuobai Zhang; Jiarui Lu; Vijil Chenthamarakshan; Aurélie C. Lozano; Payel Das; Jian Tang 005 (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 005 (CoRR, 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 001; Soham Dan; Pin-Yu Chen (CoRR, 2024)

GP-MoLFormer: A Foundation Model For Molecular Generation. - Jerret Ross; Brian Belgodere; Samuel C. Hoffman; Vijil Chenthamarakshan; Youssef Mroueh; Payel Das (CoRR, 2024)

LongFuncEval: Measuring the effectiveness of long context models for function calling. - Kiran Kate; Tejaswini Pedapati; Kinjal Basu 002; Yara Rizk; Vijil Chenthamarakshan; Subhajit Chaudhury; Mayank Agarwal; Ibrahim Abdelaziz (CoRR, 2025)

Aligning Protein Conformation Ensemble Generation with Physical Feedback. - Jiarui Lu; Xiaoyin Chen; Stephen Zhewen Lu; Aurélie C. Lozano; Vijil Chenthamarakshan; Payel Das; Jian Tang 005 (CoRR, 2025)

GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidance. - Jirí Navrátil 001; Jarret Ross; Payel Das; Youssef Mroueh; Samuel C. Hoffman; Vijil Chenthamarakshan; Brian Belgodere (CoRR, 2025)