Our publications

Pseudo-Riemannian Embedding Models for Multi-Relational Graph Representations
November 3, 2022
AKBC 2022
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
July 23, 2022
ICML 2022
On Masked Language Models for Contextual Link Prediction
May 27, 2022
ACL 2022
De novo molecular design and generative models
November 19, 2021
Science Direct
Expert-Augmented Computational Drug Repurposing Identified Baricitinib as a Treatment for COVID-19
July 28, 2021
Frontiers in Pharmacology
Directed Graph Embeddings in Pseudo-Riemannian Manifolds
July 18, 2021
ICML 2021
Learning Informative Representations of Biomedical Relations with Latent Variable Models
November 20, 2020
EMNLP | SustaiNLP 2020
Simple Hierarchical Multi-Task Neural End-To-End Entity Linking for Biomedical Text
November 20, 2020
EMNLP | LOUHI Workshop 2020
Artificial Intelligence in Drug Discovery - A New Book by Nathan Brown
November 12, 2020
Royal Society of Chemistry
Rosalind: Preclinical validation of therapeutic targets predicted by tensor factorization on heterogeneous graphs
October 26, 2020
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
July 15, 2020
Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients
June 24, 2020
EMBO Molecular Medicine
COVID-19: combining antiviral and anti-inflammatory treatments
February 27, 2020
The Lancet
DeeplyTough: Learning Structural Comparison of Protein Binding Sites
February 5, 2020
Journal of Chemical Information and modeling
Baricitinib as potential treatment for 2019-nCoV acute respiratory disease
February 4, 2020
The Lancet
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs
December 1, 2019
Neurips 2018
Biomedical relation extraction with pre-trained language representations and minimal task-specific architecture.
September 26, 2019
EMNLP 2019
Interpret: Constructing large scale biomedical knowledge bases from scratch with rapid annotation of interpretable patterns
July 2, 2019
ACL 2019
GuacaMol: Benchmarking Models for De Novo Molecular Design
March 19, 2019
Journal of Chemical Information and Modeling
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation
November 24, 2018
Neurips 2018
Adjusting for Confounding in Unsupervised Latent Representations of Images
November 15, 2018
Neurips 2018
Artificial intelligence in drug discovery
August 13, 2018
Future Medicinal Chemistry
Clinical trial design and dissemination: comprehensive analysis of clinicaltrials.gov and PubMed data since 2005
June 6, 2018
British Medical Journal
Chapter Five - Big Data in Drug Discovery
April 10, 2018
Organic synthesis provides opportunities to transform drug discovery
April 4, 2018
Nature Chemistry
Planning chemical syntheses with deep neural networks and symbolic AI
March 28, 2018
Exploring deep recurrent models with reinforcement learning for molecule design
March 27, 2018
ICLR 2018
Special Issue: Cheminformatics in Drug Discovery
March 20, 2018