Chenthamarakshan, Vijil

22 publications

ICML 2025 Aligning Protein Conformation Ensemble Generation with Physical Feedback Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

NeurIPSW 2024 Improving Structural Plausibility in 3D Molecule Generation via Property-Conditioned Training with Distorted Molecules Lucy Vost, Vijil Chenthamarakshan, Payel Das, Charlotte Deane

ICML 2024 Larimar: Large Language Models with Episodic Memory Control Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurelie Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jiri Navratil, Soham Dan, Pin-Yu Chen

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

ICLRW 2024 Structure-Informed Protein Language Model Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

NeurIPSW 2023 Characterizing Pre-Trained and Task-Adapted Molecular Representations Celia Cintas, Payel Das, Jarret Ross, Brian Belgodere, Girmaw Abebe Tadesse, Vijil Chenthamarakshan, Jannis Born, Skyler Speakman

NeurIPS 2023 Efficient Equivariant Transfer Learning from Pretrained Models Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs-Campbell, Payel Das, Lav R. Varshney

ICLRW 2023 Enhancing Protein Language Model with Structure-Based Encoder and Pre-Training Zuobai Zhang, Minghao Xu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

AAAI 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

NeurIPS 2023 Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction Zuobai Zhang, Minghao Xu, Aurelie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

ICLR 2023 Protein Representation Learning by Geometric Structure Pretraining Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

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

ECML-PKDD 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

ICMLW 2022 Protein Representation Learning by Geometric Structure Pretraining Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

ICML 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

NeurIPSW 2021 Sample-Efficient Generation of Novel Photo-Acid Generator Molecules Using a Deep Generative Model Samuel C Hoffman, Vijil Chenthamarakshan, Dmitry Zubarev, Daniel P Sanders, Payel Das

NeurIPSW 2020 Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics Yair Schiff, Payel Das, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy

NeurIPS 2020 CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models Vijil Chenthamarakshan, Payel Das, Samuel Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic

AAAI 2019 A Sequential Set Generation Method for Predicting Set-Valued Outputs Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock

ICLRW 2019 Interactive Visual Exploration of Latent Space (IVELS) for Peptide Auto-Encoder Model Selection Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt, Payel Das, Inkit Padhi, Cicero Dos Santos, Kahini Wadhawan, Vijil Chenthamarakshan

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

AAAI 2011 Transfer Latent Semantic Learning: Microblog Mining with Less Supervision Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan