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05/17/2023
Equivariant Few-Shot Learning from Pretrained Models
Efficient transfer learning algorithms are key to the success of foundat...
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03/11/2023
Enhancing Protein Language Models with Structure-based Encoder and Pre-training
Protein language models (PLMs) pre-trained on large-scale protein sequen...
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01/28/2023
Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction
Pre-training methods on proteins are recently gaining interest, leveragi...
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10/13/2022
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models
We introduce equi-tuning, a novel fine-tuning method that transforms (po...
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10/05/2022
AlphaFold Distillation for Improved Inverse Protein Folding
Inverse protein folding, i.e., designing sequences that fold into a give...
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08/13/2022
Cloud-Based Real-Time Molecular Screening Platform with MolFormer
With the prospect of automating a number of chemical tasks with high fid...
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07/08/2022
GT4SD: Generative Toolkit for Scientific Discovery
With the growing availability of data within various scientific domains,...
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05/20/2022
Learning Geometrically Disentangled Representations of Protein Folding Simulations
Massive molecular simulations of drug-target proteins have been used as ...
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04/19/2022
Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework
The COVID-19 pandemic has highlighted the urgency for developing more ef...
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03/11/2022
Protein Representation Learning by Geometric Structure Pretraining
Learning effective protein representations is critical in a variety of t...
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12/02/2021
Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
Photo-acid generators (PAGs) are compounds that release acids (H^+ ions)...
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11/12/2021
Benchmarking deep generative models for diverse antibody sequence design
Computational protein design, i.e. inferring novel and diverse protein s...
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06/24/2021
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design
Designing novel protein sequences for a desired 3D topological fold is a...
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06/17/2021
Do Large Scale Molecular Language Representations Capture Important Structural Information?
Predicting chemical properties from the structure of a molecule is of gr...
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06/08/2021
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
Deep generative models have emerged as a powerful tool for learning info...
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11/03/2020
Optimizing Molecules using Efficient Queries from Property Evaluations
Machine learning has shown potential for optimizing existing molecules w...
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10/18/2020
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics
Deep generative models are increasingly becoming integral parts of the i...
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09/23/2020
Explaining Chemical Toxicity using Missing Features
Chemical toxicity prediction using machine learning is important in drug...
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05/22/2020
Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics
De novo therapeutic design is challenged by a vast chemical repertoire a...
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05/07/2020
Learning Implicit Text Generation via Feature Matching
Generative feature matching network (GFMN) is an approach for training i...
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04/02/2020
Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
The recent COVID-19 pandemic has highlighted the need for rapid therapeu...
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03/12/2019
A Sequential Set Generation Method for Predicting Set-Valued Outputs
Consider a general machine learning setting where the output is a set of...
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10/17/2018
PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences
Given the emerging global threat of antimicrobial resistance, new method...
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05/24/2018
Fairness GAN
In this paper, we introduce the Fairness GAN, an approach for generating...
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04/22/2018
A Study on Passage Re-ranking in Embedding based Unsupervised Semantic Search
State of the art approaches for (embedding based) unsupervised semantic ...
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04/22/2018
Query Focused Variable Centroid Vectors for Passage Re-ranking in Semantic Search
In this paper, we propose a new approach for passage re-ranking. We show...
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06/28/2015
