Vijil Chenthamarakshan

71 papers A* 17A 1B 1Misc 1Journal 42Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CoFrGeNet: Continued Fraction Architectures for Language Generation. CoRR Amit Dhurandhar, Vijil Chenthamarakshan, Dennis Wei, Tejaswini Pedapati, Karthikeyan Natesan Ramamurthy, Rahul Nair
2026	A*	`conf`	GP-MoLFormer-Sim: Test Time Molecular Optimization Through Contextual Similarity Guidance. AAAI Jirí Navrátil, Jarret Ross, Payel Das, Youssef Mroueh, Samuel C. Hoffman, Vijil Chenthamarakshan, Brian Belgodere
2025	A*	`conf`	Aligning Protein Conformation Ensemble Generation with Physical Feedback. ICML Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2025	J	`jnl`	Aligning Protein Conformation Ensemble Generation with Physical Feedback. CoRR Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2025	J	`jnl`	GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidance. CoRR Jirí Navrátil, Jarret Ross, Payel Das, Youssef Mroueh, Samuel C. Hoffman, Vijil Chenthamarakshan, Brian Belgodere
2025	J	`jnl`	LongFuncEval: Measuring the effectiveness of long context models for function calling. CoRR Kiran Kate, Tejaswini Pedapati, Kinjal Basu, Yara Rizk, Vijil Chenthamarakshan, Subhajit Chaudhury, Mayank Agarwal, Ibrahim Abdelaziz
2024	J	`jnl`	GP-MoLFormer: A Foundation Model For Molecular Generation. CoRR Jerret Ross, Brian Belgodere, Samuel C. Hoffman, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2024	A*	`conf`	Larimar: Large Language Models with Episodic Memory Control. ICML Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurélie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jirí Navrátil, Soham Dan, Pin-Yu Chen
2024	J	`jnl`	Larimar: Large Language Models with Episodic Memory Control. CoRR 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
2024	A*	`conf`	Multi-Scale Representation Learning for Protein Fitness Prediction. NeurIPS Zuobai Zhang, Pascal Notin, Yining Huang, Aurélie C. Lozano, Vijil Chenthamarakshan, Debora S. Marks, Payel Das, Jian Tang
2024	J	`jnl`	Multi-Scale Representation Learning for Protein Fitness Prediction. CoRR Zuobai Zhang, Pascal Notin, Yining Huang, Aurélie C. Lozano, Vijil Chenthamarakshan, Debora S. Marks, Payel Das, Jian Tang
2024	J	`jnl`	ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation. CoRR Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2024	J	`jnl`	Structure-Informed Protein Language Model. CoRR Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2023	J	`jnl`	A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. J. Chem. Inf. Model. 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
2023	A*	`conf`	Efficient Equivariant Transfer Learning from Pretrained Models. NeurIPS Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs-Campbell, Payel Das, Lav R. Varshney
2023	J	`jnl`	Enhancing Protein Language Models with Structure-based Encoder and Pre-training. CoRR Zuobai Zhang, Minghao Xu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2023	A*	`conf`	Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. AAAI Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
2023	J	`jnl`	Equivariant Few-Shot Learning from Pretrained Models. CoRR Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Rose Driggs-Campbell, Payel Das, Lav R. Varshney
2023	J	`jnl`	Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction. CoRR Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2023	A*	`conf`	Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction. NeurIPS Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2023	A*	`conf`	Protein Representation Learning by Geometric Structure Pretraining. ICLR Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2023	A*	`conf`	Reprogramming Pretrained Language Models for Antibody Sequence Infilling. ICML Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
2022	J	`jnl`	Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework. CoRR 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
2022	J	`jnl`	AlphaFold Distillation for Improved Inverse Protein Folding. CoRR Igor Melnyk, Aurélie C. Lozano, Payel Das, Vijil Chenthamarakshan
2022	Misc	`conf`	Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
2022	—	`conf`	Cloud-Based Real-Time Molecular Screening Platform with MolFormer. ECML/PKDD (6) 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
2022	J	`jnl`	Cloud-Based Real-Time Molecular Screening Platform with MolFormer. CoRR 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
2022	J	`jnl`	Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. CoRR Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
2022	J	`jnl`	GT4SD: Generative Toolkit for Scientific Discovery. CoRR 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
2022	J	`jnl`	Large-scale chemical language representations capture molecular structure and properties. Nat. Mac. Intell. Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
2022	J	`jnl`	Learning Geometrically Disentangled Representations of Protein Folding Simulations. CoRR N. Joseph Tatro, Payel Das, Pin-Yu Chen, Vijil Chenthamarakshan, Rongjie Lai
2022	J	`jnl`	Optimizing molecules using efficient queries from property evaluations. Nat. Mach. Intell. Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das
2022	J	`jnl`	Protein Representation Learning by Geometric Structure Pretraining. CoRR Zuobai Zhang, Minghao Xu, Arian R. Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2022	J	`jnl`	Reprogramming Large Pretrained Language Models for Antibody Sequence Infilling. CoRR Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
2021	J	`jnl`	Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
2021	J	`jnl`	Benchmarking deep generative models for diverse antibody sequence design. CoRR Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurélie C. Lozano
2021	J	`jnl`	Do Large Scale Molecular Language Representations Capture Important Structural Information? CoRR Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
2021	A*	`conf`	Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. ICML Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
2021	J	`jnl`	Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. CoRR Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
2021	J	`jnl`	Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model. CoRR Samuel C. Hoffman, Vijil Chenthamarakshan, Dmitry Yu. Zubarev, Daniel P. Sanders, Payel Das
2020	J	`jnl`	Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics. CoRR 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
2020	J	`jnl`	Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das
2020	A*	`conf`	CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. NeurIPS Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic
2020	J	`jnl`	Explaining Chemical Toxicity using Missing Features. CoRR Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick
2020	A*	`conf`	Learning Implicit Text Generation via Feature Matching. ACL Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2020	J	`jnl`	Learning Implicit Text Generation via Feature Matching. CoRR Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2020	J	`jnl`	Optimizing Molecules using Efficient Queries from Property Evaluations. CoRR Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das
2020	J	`jnl`	Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. CoRR Vijil Chenthamarakshan, Payel Das, Inkit Padhi, Hendrik Strobelt, Kar Wai Lim, Benjamin Hoover, Samuel C. Hoffman, Aleksandra Mojsilovic
2019	A*	`conf`	A Sequential Set Generation Method for Predicting Set-Valued Outputs. AAAI Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
2019	J	`jnl`	A Sequential Set Generation Method for Predicting Set-Valued Outputs. CoRR Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
2019	J	`jnl`	Fairness GAN: Generating datasets with fairness properties using a generative adversarial network. IBM J. Res. Dev. Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
2019	—	`conf`	Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection. DGS@ICLR Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt, Payel Das, Inkit Padhi, Cícero Nogueira dos Santos, Kahini Wadhawan, Vijil Chenthamarakshan
2018	J	`jnl`	Fairness GAN. CoRR Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
2018	J	`jnl`	PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences. CoRR Payel Das, Kahini Wadhawan, Oscar Chang, Tom Sercu, Cícero Nogueira dos Santos, Matthew Riemer, Inkit Padhi, Vijil Chenthamarakshan, Aleksandra Mojsilovic
2018	J	`jnl`	Query Focused Variable Centroid Vectors for Passage Re-ranking in Semantic Search. CoRR Md. Faisal Mahbub Chowdhury, Vijil Chenthamarakshan, Rishav Chakravarti, Alfio Massimiliano Gliozzo
2017	—	`conf`	A cognitive assistant for risk identification and modeling. IEEE BigData Dharmashankar Subramanian, Debarun Bhattacharjya, Ruben Rodriguez Torrado, Jeffrey O. Kephart, Vijil Chenthamarakshan, Jesus Rios
2015	J	`jnl`	WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction. CoRR Vijil Chenthamarakshan, Prasad M. Deshpande, Raghu Krishnapuram, Ramakrishna Varadarajan, Knut Stolze
2014	A*	`conf`	Predicting employee expertise for talent management in the enterprise. KDD Kush R. Varshney, Vijil Chenthamarakshan, Scott W. Fancher, Jun Wang, DongPing Fang, Aleksandra Mojsilovic
2013	A*	`conf`	Amplifying the voice of youth in Africa via text analytics. KDD Prem Melville, Vijil Chenthamarakshan, Richard D. Lawrence, James Powell, Moses Mugisha, Sharad Sapra, Rajesh Anandan, Solomon Assefa
2012	—	`conf`	WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction. WAIM Vijil Chenthamarakshan, Ramakrishna Varadarajan, Prasad M. Deshpande, Raghuram Krishnapuram, Knut Stolze
2011	A*	`conf`	Concept Labeling: Building Text Classifiers with Minimal Supervision. IJCAI Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani, Richard D. Lawrence
2011	A*	`conf`	Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. AAAI Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan
2010	—	`conf`	ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. ICDM Workshops Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan
2010	J	`jnl`	Effective decision support systems for workforce deployment. IBM J. Res. Dev. 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
2010	—	`conf`	Measuring Compliance and Deviations in a Template-Based Service Contract Development Process. IEEE SCC Vijil Chenthamarakshan, Rafah Hosn, Shajith Ikbal, Nandakishore Kambhatla, Debapriyo Majumdar, Soumitra Sarkar
2010	A	`conf`	PROSPECT: a system for screening candidates for recruitment. CIKM Amit Singh, Rose Catherine, Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla
2010	B	`conf`	Syntax Based Reordering with Automatically Derived Rules for Improved Statistical Machine Translation. COLING Karthik Visweswariah, Jirí Navrátil, Jeffrey S. Sorensen, Vijil Chenthamarakshan, Nandakishore Kambhatla
2010	—	`conf`	Urdu and Hindi: Translation and sharing of linguistic resources. COLING (Posters) Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla
2009	—	`conf`	Dependency Analysis Framework for Software Service Delivery. IEEE SCC Rema Ananthanarayanan, Vijil Chenthamarakshan, Heng Chu, Prasad M. Deshpande, Raghu Krishnapuram, Shajeer K. Mohammed
2009	J	`jnl`	Leveraging social networks for corporate staffing and expert recommendation. IBM J. Res. Dev. Vijil Chenthamarakshan, Kuntal Dey, Jianying Hu, Aleksandra Mojsilovic, W. Riddle, Vikas Sindhwani
2008	—	`conf`	Rule based synonyms for entity extraction from noisy text. AND Rema Ananthanarayanan, Vijil Chenthamarakshan, Prasad M. Deshpande, Raghuram Krishnapuram