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ORCIDVijil Chenthamarakshan
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2020 – today
- 2024
[c26]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:
Larimar: Large Language Models with Episodic Memory Control. ICML 2024- [i31]Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang:
Structure-Informed Protein Language Model. CoRR abs/2402.05856 (2024) - [i30]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 abs/2402.07955 (2024) - [i29]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 abs/2403.11901 (2024) - [i28]Jerret Ross, Brian Belgodere, Samuel C. Hoffman, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das:
GP-MoLFormer: A Foundation Model For Molecular Generation. CoRR abs/2405.04912 (2024) - 2023
- [j6]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): 2960-2974 (2023) - [c25]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: 6788-6796 - [c24]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 - [c23]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: 24398-24419 - [c22]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 - [c21]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 - [i27]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 abs/2301.12068 (2023) - [i26]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 abs/2303.06275 (2023) - [i25]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 abs/2305.09900 (2023) - 2022
- [j5]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): 21-31 (2022) - [j4]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): 1256-1264 (2022) - [c20]Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das:
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP 2022: 3783-3787 - [c19]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: 641-644 - [i24]Zuobai Zhang, Minghao Xu, Arian R. Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang:
Protein Representation Learning by Geometric Structure Pretraining. CoRR abs/2203.06125 (2022) - [i23]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 abs/2204.09042 (2022) - [i22]N. Joseph Tatro, Payel Das, Pin-Yu Chen, Vijil Chenthamarakshan, Rongjie Lai:
Learning Geometrically Disentangled Representations of Protein Folding Simulations. CoRR abs/2205.10423 (2022) - [i21]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 abs/2207.03928 (2022) - [i20]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 abs/2208.06665 (2022) - [i19]Igor Melnyk, Aurélie C. Lozano, Payel Das, Vijil Chenthamarakshan:
AlphaFold Distillation for Improved Inverse Protein Folding. CoRR abs/2210.03488 (2022) - [i18]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 abs/2210.06475 (2022) - [i17]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 abs/2210.07144 (2022) - 2021
- [c18]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: 1261-1271 - [i16]Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das:
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR abs/2106.04464 (2021) - [i15]Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das:
Do Large Scale Molecular Language Representations Capture Important Structural Information? CoRR abs/2106.09553 (2021) - [i14]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 abs/2106.13058 (2021) - [i13]Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurélie C. Lozano:
Benchmarking deep generative models for diverse antibody sequence design. CoRR abs/2111.06801 (2021) - [i12]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 abs/2112.01625 (2021) - 2020
- [c17]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: 3855-3863 - [c16]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 - [i11]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 abs/2004.01215 (2020) - [i10]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 abs/2005.03588 (2020) - [i9]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 abs/2005.11248 (2020) - [i8]Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick:
Explaining Chemical Toxicity using Missing Features. CoRR abs/2009.12199 (2020) - [i7]Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das:
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR abs/2010.08548 (2020) - [i6]Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das:
Optimizing Molecules using Efficient Queries from Property Evaluations. CoRR abs/2011.01921 (2020)
2010 – 2019
- 2019
- [j3]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): 3:1-3:9 (2019) - [c15]Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock:
A Sequential Set Generation Method for Predicting Set-Valued Outputs. AAAI 2019: 2835-2842 - [c14]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 - [i5]Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock:
A Sequential Set Generation Method for Predicting Set-Valued Outputs. CoRR abs/1903.05153 (2019) - 2018
- [i4]Md. Faisal Mahbub Chowdhury, Vijil Chenthamarakshan, Rishav Chakravarti, Alfio Massimiliano Gliozzo:
Query Focused Variable Centroid Vectors for Passage Re-ranking in Semantic Search. CoRR abs/1804.08057 (2018) - [i3]Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney:
Fairness GAN. CoRR abs/1805.09910 (2018) - [i2]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 abs/1810.07743 (2018) - 2017
- [c13]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: 1570-1579 - 2015
- [i1]Vijil Chenthamarakshan, Prasad M. Deshpande, Raghu Krishnapuram, Ramakrishna Varadarajan, Knut Stolze:
WYSIWYE: An Algebra for Expressing Spatial and Textual Rules for Information Extraction. CoRR abs/1506.08454 (2015) - 2014
- [c12]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: 1729-1738 - 2013
- [c11]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: 1204-1212 - 2012
- [c10]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: 419-433 - 2011
- [c9]Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan:
Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. AAAI 2011: 561-566 - [c8]Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani, Richard D. Lawrence:
Concept Labeling: Building Text Classifiers with Minimal Supervision. IJCAI 2011: 1225-1230 - 2010
- [j2]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): 5 (2010) - [c7]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: 289-296 - [c6]Amit Singh, Rose Catherine, Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla:
PROSPECT: a system for screening candidates for recruitment. CIKM 2010: 659-668 - [c5]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: 1119-1127 - [c4]Karthik Visweswariah, Vijil Chenthamarakshan, Nandakishore Kambhatla:
Urdu and Hindi: Translation and sharing of linguistic resources. COLING (Posters) 2010: 1283-1291 - [c3]Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan:
ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. ICDM Workshops 2010: 1265-1272
2000 – 2009
- 2009
- [j1]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): 11 (2009) - [c2]Rema Ananthanarayanan, Vijil Chenthamarakshan, Heng Chu, Prasad M. Deshpande, Raghu Krishnapuram, Shajeer K. Mohammed:
Dependency Analysis Framework for Software Service Delivery. IEEE SCC 2009: 89-96 - 2008
- [c1]Rema Ananthanarayanan, Vijil Chenthamarakshan, Prasad M. Deshpande, Raghuram Krishnapuram:
Rule based synonyms for entity extraction from noisy text. AND 2008: 31-38
Coauthor Index
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last updated on 2024-10-07 22:16 CEST by the dblp team
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