Kyle Swanson

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 18

Top Topics

Convolutional Neural Network

Regression Model

Machine Learning

Monte Carlo Tree Search

Top Venues

J. Chem. Inf. Model.

Publications

Kyle Swanson, Parker Walther, Jeremy Leitz, Souhrid Mukherjee, Joseph C. Wu, Rabindra V. Shivnaraine, James Zou
ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries. Bioinform. 40 (7) (2024)
Kyle Swanson, Gary Liu, Denise B. Catacutan, Autumn Arnold, James Zou, Jonathan M. Stokes
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics. Nat. Mac. Intell. 6 (3) (2024)
John Ho, Zhao-Heng Yin, Colin Zhang, Henry Overhauser, Kyle Swanson, Yang Ha
Predicting Drug Solubility Using Different Machine Learning Methods - Linear Regression Model with Extracted Chemical Features vs Graph Convolutional Neural Network. CoRR (2023)
Kyle Swanson, Howard Chang, James Zou
Predicting Immune Escape with Pretrained Protein Language Model Embeddings. MLCB (2022)
Kyle Swanson, Joy Hsu, Mirac Suzgun
Monte Carlo Tree Search for Interpreting Stress in Natural Language. CoRR (2022)
Kyle Swanson, Joy Hsu, Mirac Suzgun
Monte Carlo Tree Search for Interpreting Stress in Natural Language. LT-EDI (2022)
Angeliki V. Katsenou, Fan Zhang, Kyle Swanson, Mariana Afonso, Joel Sole, David R. Bull
VMAF-based Bitrate Ladder Estimation for Adaptive Streaming. PCS (2021)
Lior Hirschfeld, Kyle Swanson, Kevin Yang, Regina Barzilay, Connor W. Coley
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction. J. Chem. Inf. Model. 60 (8) (2020)
Kyle Swanson, Lili Yu, Tao Lei
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport. ACL (2020)
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola
Improving Molecular Design by Stochastic Iterative Target Augmentation. CoRR (2020)
Lior Hirschfeld, Kyle Swanson, Kevin Yang, Regina Barzilay, Connor W. Coley
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction. CoRR (2020)
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola
Improving Molecular Design by Stochastic Iterative Target Augmentation. ICML (2020)
Kyle Swanson, Lili Yu, Tao Lei
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport. CoRR (2020)
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay
Correction to Analyzing Learned Molecular Representations for Property Prediction. J. Chem. Inf. Model. 59 (12) (2019)
Kyle Swanson, Lili Yu, Christopher Fox, Jeremy Wohlwend, Tao Lei
Building a Production Model for Retrieval-Based Chatbots. CoRR (2019)
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay
Are Learned Molecular Representations Ready For Prime Time? CoRR (2019)
Kirk Swanson, Shubhendu Trivedi, Joshua Lequieu, Kyle Swanson, Risi Kondor
Deep Learning for Automated Classification and Characterization of Amorphous Materials. CoRR (2019)
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay
Analyzing Learned Molecular Representations for Property Prediction. J. Chem. Inf. Model. 59 (8) (2019)