Search Results for author: Aurelie Lozano

Found 6 papers, 2 papers with code

Protein Representation Learning by Geometric Structure Pretraining

no code implementations11 Mar 2022 Zuobai Zhang, Minghao Xu, Arian Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

Learning effective protein representations is critical in a variety of tasks in biology such as predicting protein function or structure.

Contrastive Learning Representation Learning

Benchmarking deep generative models for diverse antibody sequence design

no code implementations12 Nov 2021 Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurelie Lozano

Here we consider three recently proposed deep generative frameworks for protein design: (AR) the sequence-based autoregressive generative model, (GVP) the precise structure-based graph neural network, and Fold2Seq that leverages a fuzzy and scale-free representation of a three-dimensional fold, while enforcing structure-to-sequence (and vice versa) consistency.

On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm

1 code implementation19 Oct 2018 Tsui-Wei Weng, huan zhang, Pin-Yu Chen, Aurelie Lozano, Cho-Jui Hsieh, Luca Daniel

We apply extreme value theory on the new formal robustness guarantee and the estimated robustness is called second-order CLEVER score.

Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World

1 code implementation22 Jan 2017 Sahil Garg, Irina Rish, Guillermo Cecchi, Aurelie Lozano

In this paper, we focus on online representation learning in non-stationary environments which may require continuous adaptation of model architecture.

Dictionary Learning Hippocampus +3

A General Family of Trimmed Estimators for Robust High-dimensional Data Analysis

no code implementations26 May 2016 Eunho Yang, Aurelie Lozano, Aleksandr Aravkin

We consider the problem of robustifying high-dimensional structured estimation.

Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality

no code implementations9 Aug 2014 Vikas Sindhwani, Ha Quang Minh, Aurelie Lozano

We propose a general matrix-valued multiple kernel learning framework for high-dimensional nonlinear multivariate regression problems.

Causal Inference Generalization Bounds

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