Jensun Ravichandran

According to our database, Jensun Ravichandran authored at least 9 papers between 2019 and 2022.

Collaborative distances:

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

2022

Quantum-inspired learning vector quantizers for prototype-based classification.

Thomas Villmann, Alexander Engelsberger, Jensun Ravichandran, Andrea Villmann, Marika Kaden

Neural Comput. Appl., 2022

Variants of recurrent learning vector quantization.

Jensun Ravichandran, Marika Kaden, Thomas Villmann

Neurocomputing, 2022

A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Null-Space Evaluation.

Thomas Villmann, Daniel Staps, Jensun Ravichandran, Sascha Saralajew, Michael Biehl, Marika Kaden

Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Trustworthiness and Confidence of Gait Phase Predictions in Changing Environments Using Interpretable Classifier Models.

Danny Möbius, Jensun Ravichandran, Marika Kaden, Thomas Villmann

Proceedings of the Neural Information Processing - 29th International Conference, 2022

2021

RecLVQ: Recurrent Learning Vector Quantization.

Jensun Ravichandran, Thomas Villmann, Marika Kaden

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

Variants of DropConnect in Learning vector quantization networks for evaluation of classification stability.

Jensun Ravichandran, Marika Kaden, Sascha Saralajew, Thomas Villmann

Neurocomputing, 2020

Quantum-Inspired Learning Vector Quantization for Classification Learning.

Thomas Villmann, Jensun Ravichandran, Alexander Engelsberger, Andrea Villmann, Marika Kaden

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Investigation of Activation Functions for Generalized Learning Vector Quantization.

Thomas Villmann, Jensun Ravichandran, Andrea Villmann, David Nebel, Marika Kaden

Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

DropConnect for Evaluation of Classification Stability in Learning Vector Quantization.

Jensun Ravichandran, Sascha Saralajew, Thomas Villmann

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019