Aurélie C. Lozano

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 27

Top Topics

Iterative Refinement

Physicochemical Properties

Parameter Learning

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)
Dongxia Wu, Tsuyoshi Idé, Aurélie C. Lozano, Georgios Kollias, Jirí Navrátil, Naoki Abe, Yi-An Ma, Rose Yu
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. 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)
Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. CoRR (2024)
Dongxia Wu, Tsuyoshi Idé, Georgios Kollias, Jirí Navrátil, Aurélie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. AISTATS (2024)
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
Structure-Informed Protein Language Model. CoRR (2024)
Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. ACL (Findings) (2024)
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)
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)
Aurélie C. Lozano, Hantian Ding, Naoki Abe, Alexander E. Lipka
Regularized multi-trait multi-locus linear mixed models for genome-wide association studies and genomic selection in crops. BMC Bioinform. 24 (1) (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)
Yonas Sium, Georgios Kollias, Tsuyoshi Idé, Payel Das, Naoki Abe, Aurélie C. Lozano, Qi Li
Direction Aware Positional and Structural Encoding for Directed Graph Neural Networks. ICASSP (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)
Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe
Directed Graph Auto-Encoders. CoRR (2022)
Jihun Yun, Aurélie C. Lozano, Eunho Yang
AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning. AISTATS (2022)
Igor Melnyk, Aurélie C. Lozano, Payel Das, Vijil Chenthamarakshan
AlphaFold Distillation for Improved Inverse Protein Folding. CoRR (2022)
Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe
Directed Graph Auto-Encoders. AAAI (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)
Jihun Yun, Aurélie C. Lozano, Eunho Yang
Adaptive Proximal Gradient Methods for Structured Neural Networks. NeurIPS (2021)
Kyung-Su Kim, Aurélie C. Lozano, Eunho Yang
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks. CoRR (2020)
Ming Yu, Karthikeyan Natesan Ramamurthy, Addie M. Thompson, Aurélie C. Lozano
Simultaneous Parameter Learning and Bi-clustering for Multi-Response Models. Frontiers Big Data 2 (2019)
Ming Yu, Karthikeyan Natesan Ramamurthy, Addie M. Thompson, Aurélie C. Lozano
Simultaneous Parameter Learning and Bi-Clustering for Multi-Response Models. CoRR (2018)
Meghana Kshirsagar, Eunho Yang, Aurélie C. Lozano
Learning Task Clusters via Sparsity Grouped Multitask Learning. ECML/PKDD (2) (2017)
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. CoRR (2017)
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. ICLR (Workshop) (2017)
Eunho Yang, Aurélie C. Lozano
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity. ICML (2017)
Prasanna Sattigeri, Aurélie C. Lozano, Aleksandra Mojsilovic, Kush R. Varshney, Mahmoud Naghshineh
Understanding Innovation to Drive Sustainable Development. CoRR (2016)