6 citations · 7 across the 5 of their papers we have counts for
8 papers
Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference
Antonio Khalil Moretti, Liyi Zhang, Christian A. Naesseth +3
Bayesian phylogenetic inference is often conducted via local or sequential search over topologies and branch lengths using algorithms such as random-walk Markov chain Monte Carlo (…
Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations
Iddo Drori, Darshan Thaker, Arjun Srivatsa +15
Proteins are the major building blocks of life, and actuators of almost all chemical and biophysical events in living organisms. Their native structures in turn enable their biolog…
Particle Smoothing Variational Objectives
Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu +2
A body of recent work has focused on constructing a variational family of filtered distributions using Sequential Monte Carlo (SMC). Inspired by this work, we introduce Particle Sm…
High Quality Prediction of Protein Q8 Secondary Structure by Diverse Neural Network Architectures
Iddo Drori, Isht Dwivedi, Pranav Shrestha +13
We tackle the problem of protein secondary structure prediction using a common task framework. This lead to the introduction of multiple ideas for neural architectures based on sta…
Latent Space Temporal Model of Microbial Abundance to Predict Domination and Bacteremia
Ruiqi Zhong, Tyler Joseph, Joao B Xavier +1
Gut microbial composition has been linked to multiple health outcomes. Yet, temporal analysis of this composition had been limited to deterministic models. In this paper, we introd…
Parkinson's Disease Digital Biomarker Discovery with Optimized Transitions and Inferred Markov Emissions
Avinash Bukkittu, Baihan Lin, Trung Vu +1
We search for digital biomarkers from Parkinson's Disease by observing approximate repetitive patterns matching hypothesized step and stride periodic cycles. These observations wer…