Joshua L. Phillips

According to our database, Joshua L. Phillips authored at least 21 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Conditional Forecasting of Bitcoin Prices Using Exogenous Variables.

Adel Mahfooz, Joshua L. Phillips

IEEE Access, 2024

2022

Attention Is Not Enough.

Joshua Miller, Shawheen Naderi, Chaning Mullinax, Joshua L. Phillips

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021

A Neurobiologically-inspired Deep Learning Framework for Autonomous Context Learning.

David W. Ludwig, Lucas W. Remedios, Joshua L. Phillips

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

pH Dependent Binding Energies of Broadly Neutralizing Antibodies.

Scott P. Morton, Joshua L. Phillips

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Computational Electrostatics Predict Variations in SARS-CoV-2 Spike and Human ACE2 Interactions.

Scott P. Morton, Joshua L. Phillips

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Benefits of combining dimensional attention and working memory for partially observable reinforcement learning problems.

Ngozi Omatu, Joshua L. Phillips

Proceedings of the ACM SE '21: 2021 ACM Southeast Conference, 2021

Language agnostic model: detecting islamophobic content on social media.

Heena Khan, Joshua L. Phillips

Proceedings of the ACM SE '21: 2021 ACM Southeast Conference, 2021

2020

Accelerated Protein Folding Using Greedy-Proximal A.

Ivan Syzonenko, Joshua L. Phillips

J. Chem. Inf. Model., 2020

Combined Model for Sensory-Based and Feedback-Based Task Switching: Solving Hierarchical Reinforcement Learning Problems Statically and Dynamically with Transfer Learning.

Nibraas Khan, Joshua L. Phillips

Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020

Transfer Reinforcement Learning Using Output-Gated Working Memory.

Arthur Williams, Joshua L. Phillips

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Combined Model for Partially-Observable and Non-Observable Task Switching: Solving Hierarchical Reinforcement Learning Problems.

Nibraas Khan, Joshua L. Phillips

CoRR, 2019

2018

Multilayer Context Reasoning in a Neurobiologically Inspired Working Memory Model for Cognitive Robots.

Arthur Williams, Joshua L. Phillips

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

Hybrid Spectral/Subspace Clustering of Molecular Dynamics Simulations.

Ivan Syzonenko, Joshua L. Phillips

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

Dimensionality Estimation of Protein Dynamics Using Polymer Models.

Joshua L. Phillips, Michael E. Colvin, Shawn D. Newsam

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

Sub-Class Differences of PH-Dependent HIV GP120-CD4 Interactions.

Scott P. Morton, Jonathan Howton, Joshua L. Phillips

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2017

Working Memory Concept Encoding Using Holographic Reduced Representations.

Grayson M. Dubois, Joshua L. Phillips

Proceedings of the 28th Modern Artificial Intelligence and Cognitive Science Conference 2017, 2017

High-throughput structural modeling of the HIV transmission bottleneck.

Scott P. Morton, Julie B. Phillips, Joshua L. Phillips

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Computational Modeling of pH-dependent gp120-CD4 Interactions in Founder and Chronic HIV Strains.

Jonathan Howton, Joshua L. Phillips

Proceedings of the 8th ACM International Conference on Bioinformatics, 2017

2012

Validation of computational approaches for studying disordered and unfolded protein dynamics using polymer models.

Joshua L. Phillips

PhD thesis, 2012

2011

Validating Clustering of Molecular Dynamics Simulations Using Polymer Models.

Joshua L. Phillips, Michael E. Colvin, Shawn D. Newsam

BMC Bioinform., 2011

2005

A biologically inspired working memory framework for robots.

Joshua L. Phillips, David C. Noelle

Proceedings of the IEEE International Workshop on Robot and Human Interactive Communication, 2005