Jake S. Rhodes

According to our database, Jake S. Rhodes authored at least 17 papers between 2020 and 2026.

Collaborative distances:

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

2026

Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment.

Adrien Aumon, Myriam Lizotte, Guy Wolf, Kevin R. Moon, Jake S. Rhodes

CoRR, February, 2026

Scalable Tree Ensemble Proximities in Python.

Adrien Aumon, Guy Wolf, Kevin R. Moon, Jake S. Rhodes

CoRR, January, 2026

2025

Freeze, Diffuse, Decode: Geometry-Aware Adaptation of Pretrained Transformer Embeddings for Antimicrobial Peptide Design.

Pankhil Gawade, Adam Izdebski, Myriam Lizotte, Kevin R. Moon, Jake S. Rhodes, Guy Wolf, Ewa Szczurek

CoRR, November, 2025

The Generalized Proximity Forest.

Ben Shaw, Adam G. Rustad, Sofia Pelagalli Maia, Jake S. Rhodes, Kevin R. Moon

CoRR, November, 2025

Random Forest Autoencoders for Guided Representation Learning.

Adrien Aumon, Shuang Ni, Myriam Lizotte, Guy Wolf, Kevin R. Moon, Jake S. Rhodes

CoRR, February, 2025

Random Forest Autoencoders for Guided Representation Learning.

Adrien Aumon, Shuang Ni, Myriam Lizotte, Guy Wolf, Kevin J. Moon, Jake S. Rhodes

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Label-Guided Imputation via Forest-Based Proximities for Improved Time Series Classification.

Jake S. Rhodes, Adam G. Rustad, Sofia Pelagalli Maia, Evan Thacker, Hyunmi Choi, Jose Gutierrez, Tatjana Rundek, Ben Shaw

Proceedings of the International Conference on Machine Learning and Applications, 2025

Localized Uncertainty Quantification in Random Forests via Proximities.

Jake S. Rhodes, Scott D. Brown, J. Riley Wilkinson

Proceedings of the International Conference on Machine Learning and Applications, 2025

Guided Manifold Alignment With Geometry-Regularized Twin Autoencoders.

Jake S. Rhodes, Adam G. Rustad, Marshall S. Nielsen, Morgan Chase McClellan, Dallan Gardner, Dawson Hedges

Proceedings of the IEEE International Conference on Data Mining, 2025

2024

Forest Proximities for Time Series.

Ben Shaw, Jake S. Rhodes, Soukaina Filali Boubrahimi, Kevin R. Moon

CoRR, 2024

Enhancing Supervised Visualization Through Autoencoder and Random Forest Proximities for Out-of-Sample Extension.

Shuang Ni, Adrien Aumon, Guy Wolf, Kevin R. Moon, Jake S. Rhodes

Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

Graph Integration for Diffusion-Based Manifold Alignment.

Jake S. Rhodes, Adam G. Rustad

Proceedings of the International Conference on Machine Learning and Applications, 2024

Random Forest-Supervised Manifold Alignment.

Jake S. Rhodes, Adam G. Rustad

Proceedings of the IEEE International Conference on Big Data, 2024

2023

Geometry- and Accuracy-Preserving Random Forest Proximities.

Jake S. Rhodes, Adele Cutler, Kevin R. Moon

IEEE Trans. Pattern Anal. Mach. Intell., September, 2023

Supervised Manifold Learning via Random Forest Geometry-Preserving Proximities.

Jake S. Rhodes

CoRR, 2023

2021

Random Forest-Based Diffusion Information Geometry for Supervised Visualization and Data Exploration.

Jake S. Rhodes, Adele Cutler, Guy Wolf, Kevin R. Moon

Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

2020

Supervised Visualization for Data Exploration.

Jake S. Rhodes, Adele Cutler, Guy Wolf, Kevin R. Moon

CoRR, 2020