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07/02/2023
Optimizing protein fitness using Gibbs sampling with Graph-based Smoothing
The ability to design novel proteins with higher fitness on a given task...
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05/19/2023
RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing
Reaction diagram parsing is the task of extracting reaction schemes from...
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04/08/2023
DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models
Understanding how proteins structurally interact is crucial to modern bi...
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02/05/2023
SE(3) diffusion model with application to protein backbone generation
The design of novel protein structures remains a challenge in protein en...
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10/26/2022
InfoShape: Task-Based Neural Data Shaping via Mutual Information
The use of mutual information as a tool in private data sharing has rema...
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10/14/2022
Efficiently Controlling Multiple Risks with Pareto Testing
Machine learning applications frequently come with multiple diverse obje...
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10/04/2022
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Predicting the binding structure of a small molecule ligand to a protein...
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08/25/2022
Calibrated Selective Classification
Selective classification allows models to abstain from making prediction...
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07/14/2022
Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement
Computational antibody design seeks to automatically create an antibody ...
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06/08/2022
Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
Construction of a scaffold structure that supports a desired motif, conf...
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05/28/2022
Robust Molecular Image Recognition: A Graph Generation Approach
Molecular image recognition is a fundamental task in information extract...
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04/28/2022
Learning to Split for Automatic Bias Detection
Classifiers are biased when trained on biased datasets. As a remedy, we ...
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11/15/2021
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Protein complex formation is a central problem in biology, being involve...
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10/12/2021
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Generating the periodic structure of stable materials is a long-standing...
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10/09/2021
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
Antibodies are versatile proteins that bind to pathogens like viruses an...
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06/15/2021
Learning Stable Classifiers by Transferring Unstable Features
We study transfer learning in the presence of spurious correlations. We ...
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06/04/2021
NeuraCrypt: Hiding Private Health Data via Random Neural Networks for Public Training
Balancing the needs of data privacy and predictive utility is a central ...
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05/26/2021
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
We propose Predict then Interpolate (PI), a simple algorithm for learnin...
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04/18/2021
Generating Related Work
Communicating new research ideas involves highlighting similarities and ...
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04/08/2021
Nutribullets Hybrid: Multi-document Health Summarization
We present a method for generating comparative summaries that highlights...
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03/22/2021
Nutri-bullets: Summarizing Health Studies by Composing Segments
We introduce Nutri-bullets, a multi-document summarization task for heal...
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03/15/2021
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence
Typical fact verification models use retrieved written evidence to verif...
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02/17/2021
Few-shot Conformal Prediction with Auxiliary Tasks
We develop a novel approach to conformal prediction when the target task...
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11/09/2020
CapWAP: Captioning with a Purpose
The traditional image captioning task uses generic reference captions to...
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11/09/2020
Modeling Drug Combinations based on Molecular Structures and Biological Targets
Drug combinations play an important role in therapeutics due to its bett...
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10/21/2020
Deciphering Undersegmented Ancient Scripts Using Phonetic Prior
Most undeciphered lost languages exhibit two characteristics that pose s...
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07/06/2020
Relaxed Conformal Prediction Cascades for Efficient Inference Over Many Labels
Providing a small set of promising candidates in place of a single predi...
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06/15/2020
Improved Conditional Flow Models for Molecule to Image Synthesis
In this paper, we aim to synthesize cell microscopy images under differe...
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06/12/2020
Learning Graph Models for Template-Free Retrosynthesis
Retrosynthesis prediction is a fundamental problem in organic synthesis,...
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06/08/2020
Optimal Transport Graph Neural Networks
Current graph neural network (GNN) architectures naively average or sum ...
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06/06/2020
Domain Extrapolation via Regret Minimization
Many real prediction tasks such as molecular property prediction require...
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05/20/2020
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Uncertainty quantification (UQ) is an important component of molecular p...
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05/05/2020
Adaptive Invariance for Molecule Property Prediction
Effective property prediction methods can help accelerate the search for...
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02/11/2020
Improving Molecular Design by Stochastic Iterative Target Augmentation
Generative models in molecular design tend to be richly parameterized, d...
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02/08/2020
Composing Molecules with Multiple Property Constraints
Drug discovery aims to find novel compounds with specified chemical prop...
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02/08/2020
Hierarchical Generation of Molecular Graphs using Structural Motifs
Graph generation techniques are increasingly being adopted for drug disc...
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02/08/2020
Blank Language Models
We propose Blank Language Model (BLM), a model that generates sequences ...
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10/22/2019
Capturing Greater Context for Question Generation
Automatic question generation can benefit many applications ranging from...
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10/21/2019
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis
We propose a new model for making generalizable and diverse retrosynthet...
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09/30/2019
Automatic Fact-guided Sentence Modification
Online encyclopediae like Wikipedia contain large amounts of text that n...
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09/20/2019
Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
This paper explores the task of leveraging typology in the context of cr...
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08/26/2019
Are We Safe Yet? The Limitations of Distributional Features for Fake News Detection
Automatic detection of fake news — texts that are deceitful and misleadi...
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08/16/2019
Few-shot Text Classification with Distributional Signatures
In this paper, we explore meta-learning for few-shot text classification...
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08/14/2019
Towards Debiasing Fact Verification Models
Fact verification requires validating a claim in the context of evidence...
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06/16/2019
Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
In this paper we propose a novel neural approach for automatic decipherm...
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05/29/2019
Latent Space Secrets of Denoising Text-Autoencoders
While neural language models have recently demonstrated impressive perfo...
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05/29/2019
Path-Augmented Graph Transformer Network
Much of the recent work on learning molecular representations has been b...
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04/24/2019
Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes
PURPOSE: The medical literature relevant to germline genetics is growing...
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04/02/2019
Inferring Which Medical Treatments Work from Reports of Clinical Trials
How do we know if a particular medical treatment actually works? Ideally...
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04/02/2019
